{"as_of":"2026-08-08T04:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5192722d52f1e96c5b03fd51bef7b054a3b0fd3a01fcd24fa35bf04515566fa7","coverage":[{"denominator":84,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":84,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:41:56.198062Z","state":"measured"},{"denominator":85,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":85,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-16T20:53:49.574163Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-16T20:58:32.086377Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"cited_work":{"arxiv_id":"2505.23753","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.23753","snapshot_observed_at":"2026-07-14T01:20:44.049159Z","title":"Glaubitz and A","venue":null,"work_id":"dfdbfd34-517d-420e-8931-e1db677b88d3","year":2024},"citing_paper":{"arxiv_id":"2512.17038","last_updated":"2026-04-10T16:53:31Z","snapshot_observed_at":"2026-07-06T22:39:28.855621Z","submitted_at":"2025-12-18T20:01:44Z","title":"Do Generalized-Gamma Scale Mixtures of Normals Fit Large Image Datasets?","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-16T20:53:49.574163Z"},"links":{"cited_paper":"/paper/2505.23753","citing_paper":"/paper/2512.17038"},"observation_digest":"sha256:1ef8883aaf29b2fe2609141e5a2f901fda176b0df17f7c689d9faa3e6986bb8a","observation_id":"93aa7c45-9262-4efc-bea7-fa27678ec7ac","resolution":{"observed_at":"2026-07-14T01:20:44.049159Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.23753/citation-record","integrity":"/paper/2505.23753/integrity","json":"/paper/2505.23753/citation-record.json","paper":"/paper/2505.23753"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:49.282328Z","title":"Agapiou, J","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:49.282328Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f188d974c0c976df397443db6239d790d0bdd268e27de7aede335018821fd00e","observation_id":"57bccfe8-272b-491f-9edb-8ac48ae4d4bd","resolution":{"observed_at":"2026-08-07T12:41:49.282328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:49.395247Z","title":"Ambrosio and N","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:49.395247Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:16b50faf468738e3f896e48cf9d13ee5bb17cb7b9ea3bfc89d04cc88776e131a","observation_id":"1f686904-8340-4038-a041-f31478c142c2","resolution":{"observed_at":"2026-08-07T12:41:49.395247Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:49.470748Z","title":null,"venue":null,"work_id":null,"year":1974},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:49.470748Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:57319e4a060637c5bbacb2d6a93da96fc2b4692dc895c58f48efe71846499258","observation_id":"38daeb2c-b0f5-48fe-bde6-b1c3e8d78737","resolution":{"observed_at":"2026-08-07T12:41:49.470748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:49.563554Z","title":"Andrieu and J","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:49.563554Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:9fa2d5c857b36cc62565b421eca5b67e545e947996695a3a639f04da34df1025","observation_id":"fbfa74ea-655a-42e0-910b-49f18e9bd80b","resolution":{"observed_at":"2026-08-07T12:41:49.563554Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:49.639014Z","title":"Ascolani, G","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:49.639014Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:e7a15491d25b2c45138bf8154f9cf893984ba0b2045b4e441d561bddddb0fa78","observation_id":"dee91e18-8f44-4441-b739-9f547652d3ff","resolution":{"observed_at":"2026-08-07T12:41:49.639014Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:09.001846Z","title":"Atchad´e and G","venue":null,"work_id":"7e67dfbb-0fd4-4bd6-8286-9ead3c66a10b","year":2010},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:49.742665Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f3bc454290566d8dd661296dbd6eca55c0dc6aef7f4d4d3c276015ac5daf9c09","observation_id":"a2be20ef-34da-42f4-b4c1-b96073ddcba4","resolution":{"observed_at":"2026-08-07T12:42:09.070907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:08.829976Z","title":null,"venue":null,"work_id":"a692d515-2088-45c7-b860-3dedf4e73d22","year":2006},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:49.796769Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:a4a8a5e150d5adec6c5c467233e647bf1b82a553a329357ebb1ac2130b9e5365","observation_id":"0a18b9ca-cb60-4eaf-86f5-d23493cb29c0","resolution":{"observed_at":"2026-08-07T12:42:08.906810Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:08.634132Z","title":null,"venue":null,"work_id":"0c69ac78-a050-431e-b97d-ee9719edebe3","year":2006},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:49.903163Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f068c9a8ac7c80868e22dcfbacf0b2f8449adc8a24bc69c45b7d47ac3c152e3c","observation_id":"15664120-f172-40e0-800a-6fd91f173814","resolution":{"observed_at":"2026-08-07T12:42:08.710299Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:08.396425Z","title":null,"venue":null,"work_id":"f505fdb7-cab1-4953-aa26-80ad55d8a8d2","year":2009},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.010333Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:4f524cf0b5f65f11d413ad16209a78c13b013e7d6414cef353a7d8876c25c717","observation_id":"f347b173-244b-4e0f-8dbf-1289dc22d7db","resolution":{"observed_at":"2026-08-07T12:42:08.502366Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:08.127306Z","title":"Baptista, Y","venue":null,"work_id":"8e21b5e7-9248-4f3e-91cf-417a83d39488","year":2023},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.113669Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:96fe205837ee9d2439bfa97905dbadeccf763d73abad10ff46279433eb16bf28","observation_id":"62e826f3-0fd8-425f-a2d5-064a3279253e","resolution":{"observed_at":"2026-08-07T12:42:08.246312Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:07.903694Z","title":null,"venue":null,"work_id":"9a64590c-a4ae-44d6-8b5c-a000bccafb50","year":1959},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.183057Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:cdf5e10bab831fb67bd3b5244c2af2eb903614e93824359d1b5385b7f03a1390","observation_id":"db367d05-9dfe-4a87-99b0-d6251d17ab9d","resolution":{"observed_at":"2026-08-07T12:42:07.989675Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:07.590932Z","title":"Beskos, M","venue":null,"work_id":"b04693e7-314c-4b61-9351-991223dcd537","year":2017},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.280891Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:5896820045e5181fbf912f391012b2424099985c9b0396174ee8413188a208c2","observation_id":"204e189b-c10f-4490-9a3c-a6ea46845dc4","resolution":{"observed_at":"2026-08-07T12:42:07.713121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:07.363517Z","title":"Beskos, N","venue":null,"work_id":"932803e8-5d72-4ffa-891f-20351748bd97","year":2013},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.370396Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:2413bdf9dedc0f7302174ba6748878362940896bee5367e28916ff789301f749","observation_id":"3dbf4374-bcaf-4d66-9cac-034371209e33","resolution":{"observed_at":"2026-08-07T12:42:07.471705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:07.082879Z","title":"Bezanson, A","venue":null,"work_id":"ef3afafa-fdd7-4959-aa55-63a8bbe65489","year":2017},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.476563Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:894328bd74be31630c5408f65e980f13f23c01a09da62af21259a9186171039d","observation_id":"7889054c-95a6-46e6-8694-8b881c49e96a","resolution":{"observed_at":"2026-08-07T12:42:07.204544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:06.765444Z","title":null,"venue":null,"work_id":"baa1558b-256d-4c41-a16e-03b835fbe3a5","year":2005},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.556413Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:518062b29de0df6550e9fbd869360b2c708141ebbb2c6580ef4657eca8b0fab2","observation_id":"f44373ae-7053-4745-9726-5eb58b578ab9","resolution":{"observed_at":"2026-08-07T12:42:06.909295Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:06.537793Z","title":"Brooks, A","venue":null,"work_id":"a7275b53-5b96-404c-ac6b-1a194fe7b797","year":2011},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.656948Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:4706c233e09dd5da555c8d2d9693727ed30e2016e1411610633a1f90c31cb41c","observation_id":"90b9718b-1443-49f7-9849-63ac61f5c758","resolution":{"observed_at":"2026-08-07T12:42:06.610621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:06.394540Z","title":null,"venue":null,"work_id":"9b608091-4e0b-46d0-b6f2-da3f567d7524","year":1998},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.731885Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:2c9ba0aa307e534114047a9bfded312336499f545ba2a059efef4bad4f446782","observation_id":"20d7e455-c437-4bb6-9376-fa89d0e06892","resolution":{"observed_at":"2026-08-07T12:42:06.458615Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:06.223627Z","title":"Cabezas and C","venue":null,"work_id":"9b5db384-c021-49ec-83ea-5ce50c54ef54","year":2023},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.843120Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:83961afd15d4acca67f7391475f2722f4e9707504c570779f186b8f1897fc09f","observation_id":"f1d63bbe-fddc-40a2-9611-a180e4e96b06","resolution":{"observed_at":"2026-08-07T12:42:06.295855Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:06.094944Z","title":"Calvetti, M","venue":null,"work_id":"16a683fe-00c2-4e11-b3cd-2ff8f5b818bf","year":2020},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:50.948029Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:3d569166b34accf64cc5ef13d81d9d4a50ec3b2e0f0a776af06f6b1ec664681a","observation_id":"dc9c2c8b-caca-4690-8d6d-04645f53de7b","resolution":{"observed_at":"2026-08-07T12:42:06.146019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:05.920993Z","title":"Calvetti, M","venue":null,"work_id":"5437bedc-6955-4388-bb49-85ecaf1a1d66","year":2020},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.045254Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:9a63f8656800384ba7b5e7abf6aeeb1d13fda1d957b76998878e98daba211cd7","observation_id":"2cf79f9a-86d9-4866-8c50-f9aaf7321e50","resolution":{"observed_at":"2026-08-07T12:42:05.996702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:05.806119Z","title":"Calvetti and E","venue":null,"work_id":"9af1f656-b0e4-4865-b84c-9d14167d74f4","year":2007},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.095510Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:e266513e90dcb6e5d24ec2b9e725d7ceafe14ffd436e45d9ce0e3e58b7307202","observation_id":"f427dbbf-3cee-4257-91a6-c8b8ba18577d","resolution":{"observed_at":"2026-08-07T12:42:05.847071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:05.641078Z","title":"Calvetti and E","venue":null,"work_id":"768d482b-db34-4d38-8ff7-1604efe6857e","year":2023},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.155200Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:9ba84670e731ab92bcac58740c89768d9a0141122da90db316a7ed23706a458d","observation_id":"025155c4-cfc2-408f-bfdc-83bede058ed5","resolution":{"observed_at":"2026-08-07T12:42:05.748860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:05.467736Z","title":"Calvetti and E","venue":null,"work_id":"7d5196bd-0300-40f4-988e-4dd92968e58a","year":2024},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.273016Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:d407da08528e21138fa1e81e04c9ba0b6c025d9526a3a5b87b5151e3def4f038","observation_id":"3a92fccf-6dea-4f40-a400-fbf19d83090f","resolution":{"observed_at":"2026-08-07T12:42:05.537668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:05.401188Z","title":"Calvetti, E","venue":null,"work_id":"a162a3e7-b87f-407c-99ca-040e0ef47f16","year":2019},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.371905Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:1648356059023dd3bb5f0fc5af10d9e35e25241855b44d4d2d51524565d41b75","observation_id":"d6b1c997-5bf6-40cf-b0fc-d0abb3affd45","resolution":{"observed_at":"2026-08-07T12:42:05.450434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:05.267235Z","title":null,"venue":null,"work_id":"b5616439-4270-44ae-bd2a-dd29e12f65ec","year":2009},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.439502Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:6c5bef3967c6bf3c304f1d824146464f473bba84b96d711439c52e7fe31a9dbf","observation_id":"499abd4e-8137-4358-a999-88e500ada6de","resolution":{"observed_at":"2026-08-07T12:42:05.321568Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:05.130555Z","title":null,"venue":null,"work_id":"3806c1a4-7c69-41b6-a2fe-d298ce3d4b5a","year":2018},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.556994Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:4dfbeac311f1185709ec182b337603b7928a57a172542671f7d254a67a070130","observation_id":"8ff2742d-1caa-4902-9165-9d3104b8916d","resolution":{"observed_at":"2026-08-07T12:42:05.182568Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.03344","last_updated":"2019-03-24T17:46:37Z","snapshot_observed_at":"2026-08-03T06:28:58.675437Z","submitted_at":"2018-03-09T01:02:47Z","title":"Dimension-Robust MCMC in Bayesian Inverse Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.03344","snapshot_observed_at":"2026-08-07T12:41:51.627211Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.627211Z"},"links":{"cited_paper":"/paper/1803.03344","citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:ee84a81dd1e5f5deb9e341a8e4fc7fb799a173e33147beaad5778388a528fc4e","observation_id":"54fd0065-4835-49b4-b68f-a9cf72d85df4","resolution":{"observed_at":"2026-08-07T12:41:51.627211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:04.949055Z","title":"Churchill and A","venue":null,"work_id":"0a4dfb29-ba28-46d9-9937-d5f83fd6f5d6","year":2022},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.714114Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f5dbf4bdf7aec7c810b88f3ce927d4647fe4ccbf9b9d32bb68b4db34c2dd8b8c","observation_id":"6fa01586-584b-41f1-bb57-c6b08ff959e3","resolution":{"observed_at":"2026-08-07T12:42:05.051075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:04.770517Z","title":"Cotter, G","venue":null,"work_id":"c35ed1bf-8d4c-43bb-a036-d74e4a0fbe2f","year":2013},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.787933Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:51f3941dc854914a4c3763a642c910575923c95990f118236c63947edd54310b","observation_id":"f429d037-5ad2-4bee-b644-0c931256b9ca","resolution":{"observed_at":"2026-08-07T12:42:04.833151Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:04.627095Z","title":null,"venue":null,"work_id":"08c1692c-c831-47a1-b633-854bb73ecdbf","year":2022},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.855311Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:fb38f6c408a8ac0b950983bedfeffcfe91c33c2fe3b02bbde87d072e6934559b","observation_id":"250fffa4-ba5c-41e2-bce8-9fa273beea90","resolution":{"observed_at":"2026-08-07T12:42:04.689998Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:04.507866Z","title":"https://dlmf.nist.gov/, Release 1.2.0 of 2024-03-15","venue":null,"work_id":"ec9d3511-0723-402c-893c-9df09cc910f4","year":2024},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:51.976011Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:07fa443e1976832081f7c25a64ca1f5547efa12e52b35598cf71bb06d9b85969","observation_id":"8e78095c-4681-4347-bff1-2645c22deba7","resolution":{"observed_at":"2026-08-07T12:42:04.558602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:04.398884Z","title":"Dong and M","venue":null,"work_id":"18f1f53f-47fa-480f-ab3f-1b0857368ab1","year":2023},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.067758Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:cff6a051552b21b547cf7b331a08b2f89676091fa408bdb9eb764a30a140f136","observation_id":"1bdf0d9b-8554-4bff-bad6-3effcc91fbaf","resolution":{"observed_at":"2026-08-07T12:42:04.445766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:04.293928Z","title":null,"venue":null,"work_id":"71c3d89d-b28d-4d73-a47d-f332b6d21a5e","year":2020},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.128207Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f8c42ea1c9e52e19a72b4919aa296a88b4cf02345c173acbd9056a8e744cea4f","observation_id":"120ee719-81f7-4264-992a-8a55c2c72a1e","resolution":{"observed_at":"2026-08-07T12:42:04.335513Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:04.177325Z","title":null,"venue":null,"work_id":"2632b81d-330e-43ce-96cc-25364921686b","year":2007},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.200946Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:da37b9bdb20d1375f4c64dd8c455e4b7e5d3ebebd7fca8ae64d76454eae728bc","observation_id":"6fe2dc8a-2666-45e2-9207-1c9a627a80a8","resolution":{"observed_at":"2026-08-07T12:42:04.218500Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:04.075767Z","title":"Fleischer , Transformations for accelerating MCMC simulations with broken ergodicity , in 2007 Winter Simulation Conference, IEEE, 2007, pp","venue":null,"work_id":"bfb3a7ce-133f-45fb-869d-9d737347ad95","year":2007},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.277334Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f76fa383fd21c2a9cc4da6fb7c94fe88e80864204243f8c423dacb40bbacbf95","observation_id":"e0292d70-d4fa-4bb3-8bbb-47a4db8a01fe","resolution":{"observed_at":"2026-08-07T12:42:04.122578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:03.965403Z","title":"Flock, Y","venue":null,"work_id":"b985a394-f891-452b-9cda-bc89ff1230ff","year":2024},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.372075Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:595f629843782e054c3a2bc3c93dcbbc7a02021033b26ebce65b7f8d481814f2","observation_id":"6ece7e2a-ae05-4184-ad0c-5b675c53f91d","resolution":{"observed_at":"2026-08-07T12:42:04.013988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:03.854395Z","title":"Gelman, J","venue":null,"work_id":"5f953d19-c1b1-4826-b921-b37aba8d7bd7","year":2003},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.461807Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:951e53eddbce0ed3dccb3c1d588fbc017132a6bda7a25e56c29b56d4ddb520f6","observation_id":"77344348-674b-40cb-a8c3-6e09c6df90f9","resolution":{"observed_at":"2026-08-07T12:42:03.899832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:03.725679Z","title":"Gelman and D","venue":null,"work_id":"799f05b6-12d1-4e07-a45e-c8f6ece7eaa2","year":1992},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.553964Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:c021f1e892d038a0d04c35e2ed2320601ea0232de60b7fe9d63c40eb92dc144d","observation_id":"1cf71c29-cd26-4a08-b9b6-3f31b1f07163","resolution":{"observed_at":"2026-08-07T12:42:03.789590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:03.538303Z","title":"Glaubitz and A","venue":null,"work_id":"589f613a-16af-4645-a4cf-07c5c7a88ecf","year":2024},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.670238Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:4d3882f36c4d48e3bd43310eb0d6791a7812290863c32f7d97b52f39c50087c0","observation_id":"e1cfe133-375a-475c-8392-6872b44d87fc","resolution":{"observed_at":"2026-08-07T12:42:03.625200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:03.389004Z","title":"Glaubitz, A","venue":null,"work_id":"3ed89a85-dd0f-4ba9-8904-42845ee09a6d","year":2023},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.741085Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:9f1e34d6497fea9053596387d04b925fe153bda6e7dca0a6e9b97234918202cb","observation_id":"26412c89-89ec-4d2f-8df4-8e5f59217595","resolution":{"observed_at":"2026-08-07T12:42:03.457272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:03.185704Z","title":"Gom `es, C","venue":null,"work_id":"5f29ddb2-789a-41d4-a880-9ee9a73b433f","year":2008},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.841458Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:94b3c17e6df45d32b4821e430b50c60a20d941cbcf2394354c439e1ea15afd6e","observation_id":"f8e45ef7-5f75-4c4a-946b-f121f71da588","resolution":{"observed_at":"2026-08-07T12:42:03.289184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:03.020157Z","title":"Haario, E","venue":null,"work_id":"c7bb62fb-d266-4a2c-9fa5-b72830675972","year":2001},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:52.933894Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:74f601db31a94067af7310c3bdd09cea644da650f9794e88a1bd35b27822dd1d","observation_id":"b1c426fc-121a-441e-abaf-a86ca20bfe4b","resolution":{"observed_at":"2026-08-07T12:42:03.111676Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:02.859078Z","title":"Kaipio and E","venue":null,"work_id":"e0a7c50b-b995-4798-a1b3-c93da6fe59c6","year":2007},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.001038Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:2636a4ae230f7ac381b8d18901c2bdd398b735a116422ab769485423e6e4ace5","observation_id":"febc0b14-e840-477d-90a3-e5411eef11e6","resolution":{"observed_at":"2026-08-07T12:42:02.928908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:02.662779Z","title":"Knothe, Contributions to the theory of convex bodies","venue":null,"work_id":"c96e56ee-1297-4cf5-be41-d13b3330ef0c","year":1957},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.064541Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f4dd55d9f2e767eb8165d0721cf27f6cea39a549823adedcae94b5c74abcae35","observation_id":"02dcd6ed-e5cb-486a-8d93-c30ce88a9179","resolution":{"observed_at":"2026-08-07T12:42:02.742820Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:02.465476Z","title":"Lindbloom, J","venue":null,"work_id":"7d90a58a-ceaa-426a-8b3d-1427273dff00","year":2025},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.122140Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:61963564bcc260df80317da93a8a899f5f60e3c0d6b2a34a63cd92b004c93678","observation_id":"663d3006-9140-4042-aacb-4cb6c0c0e1e1","resolution":{"observed_at":"2026-08-07T12:42:02.558833Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.01827","last_updated":"2025-05-03T14:06:36Z","snapshot_observed_at":"2026-08-07T15:56:47.586032Z","submitted_at":"2025-05-03T14:06:36Z","title":"Priorconditioned Sparsity-Promoting Projection Methods for Deterministic and Bayesian Linear Inverse Problems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.01827","snapshot_observed_at":"2026-08-07T12:41:53.224470Z","title":"Lindbloom, M","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.224470Z"},"links":{"cited_paper":"/paper/2505.01827","citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:985ef9624e4aadf19a3092457aedacc21dc507083fb601ad1d5d0e503507bd56","observation_id":"900e7db9-5d95-45d7-83f3-3bebdaff36de","resolution":{"observed_at":"2026-08-07T12:41:53.224470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:02.283179Z","title":null,"venue":null,"work_id":"5714435f-f9b7-4801-b60d-109df72c415e","year":2013},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.297626Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:bd00c52f0b0d4f568333cf89722cc7327275ff2983e95f88e918f2014f1108d4","observation_id":"14213644-abdf-4eea-bf94-0bb7ab593d70","resolution":{"observed_at":"2026-08-07T12:42:02.341964Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:02.094145Z","title":"Markkanen, L","venue":null,"work_id":"11bb2042-9db3-4080-a09d-f2ebd00ee316","year":2019},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.382412Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:924ed7628b63042efd9a841667b5a435e3ff5e1e84b1b994a45c408d37138c98","observation_id":"8df72c29-e72f-4e61-bea6-b608cfac6653","resolution":{"observed_at":"2026-08-07T12:42:02.183079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:01.968294Z","title":"Marshall and G","venue":null,"work_id":"25aa3899-bd73-4ad7-86d0-beb19a8b678d","year":2012},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.474652Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:37372c4006bc3c46138e6f17b98586e0954344b03e117fae7efac14bac12d371","observation_id":"8187e2f3-b336-4b3a-974c-37cfc79e293f","resolution":{"observed_at":"2026-08-07T12:42:02.029452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:01.820148Z","title":"Marzouk, T","venue":null,"work_id":"3147847b-ef76-4ce6-913d-484f3c8c5867","year":2016},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.565882Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:96b7b798f0aedbd431ea26a5c6f20baa2af158a6d0d9362ddf0bdafa9e8d2881","observation_id":"4e6e6c8a-e7c5-450e-983e-7d09f1efdf09","resolution":{"observed_at":"2026-08-07T12:42:01.894931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:01.659443Z","title":"Murray, R","venue":null,"work_id":"69cc5380-5feb-4256-8026-4f1ed7f5f51c","year":2010},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.655831Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:09b4a4f853a38155ffbc1fab33df4be90d3625b4cb4d95f1a6e78ed546a1a13f","observation_id":"32b36bcd-67f3-4a99-a87f-7fe5d86e4cf0","resolution":{"observed_at":"2026-08-07T12:42:01.747450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:01.527680Z","title":"Nishihara, I","venue":null,"work_id":"85af0617-2a26-46f4-9f08-b60680126622","year":2014},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.749002Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:70e7054a6bea38a88d3b5e50487c37e9581e366028eae278105f960a3376e9d7","observation_id":"118cbdfe-f589-4921-ab41-dd6afe84b2e7","resolution":{"observed_at":"2026-08-07T12:42:01.586297Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:01.387149Z","title":"Nocedal and S","venue":null,"work_id":"f0dc9704-3175-478e-aacd-c6a65053b938","year":2006},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.840937Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:ac6562a4ff8114f30e9e9417d94b69a709297f3bb072f4a4fe6f212ec6697461","observation_id":"7253b3f7-f909-48d1-bbde-fce63ce147de","resolution":{"observed_at":"2026-08-07T12:42:01.452423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:01.239259Z","title":"Papaspiliopoulos, G","venue":null,"work_id":"d24e00c7-8141-4c24-b6bb-3a4cab97188a","year":2003},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:53.948282Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f20bdd58df09fd31573861b30ddbded3a6936ef3bf9c185e5a70308f7d910124","observation_id":"3ce9eeff-60d2-45ef-ac01-fc767e077801","resolution":{"observed_at":"2026-08-07T12:42:01.297966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:01.107694Z","title":"Papaspiliopoulos, G","venue":null,"work_id":"e8edafe8-165c-40d8-8a48-a4066854d89a","year":2007},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.039194Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:a9552a7375a575c62c3b0d17f0ddf92d33037ba20062af01abbe4ae6cb5b68dc","observation_id":"3ee25880-9ff1-4e3e-98c6-919a8718cf57","resolution":{"observed_at":"2026-08-07T12:42:01.164569Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:00.959279Z","title":"Park and G","venue":null,"work_id":"9ae8a7f7-90f6-4546-9f39-8ec134686418","year":2008},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.072739Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:fc819f0c12c24d426705bdc99f9c2e1d3347ca6edf33c9b192ffa94f636bc732","observation_id":"641b006c-96f0-4f82-b503-0c559d557994","resolution":{"observed_at":"2026-08-07T12:42:01.032951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:00.828906Z","title":null,"venue":null,"work_id":"fcbdce7e-fe51-42ba-9e36-621409474796","year":2018},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.119831Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:b959ff481ded6103083f85762042e72a626ee1be93a13d6c690817542557b3c6","observation_id":"043ced58-3a78-419b-b84f-3a65fccec617","resolution":{"observed_at":"2026-08-07T12:42:00.888051Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:00.670043Z","title":null,"venue":null,"work_id":"a114c0c4-9f1e-4bbc-a9b8-e03ace5d1bbe","year":2015},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.188247Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f54c3101abc13dab5239046ab1fa345c9d3790605ba1db21e36ac89bb6166d84","observation_id":"d68837f3-1f74-444d-83fb-c0b6a43c84d1","resolution":{"observed_at":"2026-08-07T12:42:00.747602Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:00.521209Z","title":"Rackauckas and Q","venue":null,"work_id":"d290e575-6329-4f87-918c-cb8476eed51d","year":2017},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.265547Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:ebe3c250fb8f05e80b757dacbb965f3b7b7e2103050e41e5bd708fef879bf292","observation_id":"3144098b-f4a0-49aa-9c6f-8fd8511f286d","resolution":{"observed_at":"2026-08-07T12:42:00.588080Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:00.384479Z","title":"Ranocha, M","venue":null,"work_id":"77203f7f-e2bb-4315-bd6e-255550fa41cc","year":2022},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.326787Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:503b52083cc7ef5e79ca264d6d1e3ac588d770284e06ca4e546f80899f81b7eb","observation_id":"3c57d604-1af2-4de2-b9a7-d998e3da6b48","resolution":{"observed_at":"2026-08-07T12:42:00.431279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:00.217076Z","title":"Ranocha, A","venue":null,"work_id":"c6fe5474-1705-494a-aaf3-15f9956c8187","year":2025},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.358077Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:6cb4edb6fe7fc9d6531b4e6816c5dfbd6561a6f7c457666f6b7435da3046a51d","observation_id":"02404c72-3a16-4fb0-9f95-dfa38e5b7a0d","resolution":{"observed_at":"2026-08-07T12:42:00.304211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:42:00.051795Z","title":"Rezende and S","venue":null,"work_id":"b23aa3c4-ee9f-413e-85cc-87844a46ae4e","year":2015},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.366637Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:c35097b566e054442d05a07974819d1b2256d254c65e9ee466a56b85dfb5aa62","observation_id":"001a38dc-1e9e-41cf-8e86-565a8e42daf9","resolution":{"observed_at":"2026-08-07T12:42:00.148256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:59.858207Z","title":"Robert and G","venue":null,"work_id":"925bb02c-4fed-4b90-a68a-bed8f35bcd6b","year":2013},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.537936Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:eba079cc2d7f994218f6bcd8fd61269bcf9d9f80ca912febeaf6eac543c5eefd","observation_id":"fabe3fdd-026d-495b-b4dd-1ab550b1d239","resolution":{"observed_at":"2026-08-07T12:41:59.943469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:59.689168Z","title":null,"venue":null,"work_id":"0f0503d6-ed2b-477c-8f8b-424e99efa709","year":1998},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.660001Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:fab4f7672101534d0d0a437ca986149343d6c280afa7ad03a05000d4bf1a9d8d","observation_id":"88335d52-9da3-4426-8744-011d1baa1319","resolution":{"observed_at":"2026-08-07T12:41:59.777015Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:59.526740Z","title":"Rosenblatt, Remarks on a multivariate transformation , The Annals of Mathematical Statistics, 23 (1952), pp","venue":null,"work_id":"6245f862-4785-4ba9-982c-50b777921e20","year":1952},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.809013Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:0f0a056d580f005b0ca62b40ef81f432cdb8c4e938769abd68f5945749e0e836","observation_id":"56dbdc3d-d102-44d6-99db-803cda6bea15","resolution":{"observed_at":"2026-08-07T12:41:59.591571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:59.325365Z","title":"Santambrogio, Optimal Transport for Applied Mathematicians , Springer, 2015","venue":null,"work_id":"e66ea46f-b9f9-4a3a-8848-f5bc9313e77b","year":2015},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:54.961598Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:0934ca73fa7cbb1db014b57451cff97c21d562b8a1bf88222552d8600e129070","observation_id":"5131bdfa-3118-4be6-af69-db15358078f7","resolution":{"observed_at":"2026-08-07T12:41:59.422412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16359","last_updated":"2024-05-25T21:52:07Z","snapshot_observed_at":"2026-08-04T20:41:42.261097Z","submitted_at":"2024-05-25T21:52:07Z","title":"A First Course in Monte Carlo Methods","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16359","snapshot_observed_at":"2026-08-07T12:41:55.174304Z","title":"Sanz-Alonso and O","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.174304Z"},"links":{"cited_paper":"/paper/2405.16359","citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:e50919c57391d78457b08bd1f73e2530d0fd1161e22f61e1d1da3c6e3ce69257","observation_id":"b96d275b-693b-4238-97b8-e6912af4be96","resolution":{"observed_at":"2026-08-07T12:41:55.174304Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03074","last_updated":"2024-01-05T22:13:41Z","snapshot_observed_at":"2026-07-06T17:12:10.787061Z","submitted_at":"2024-01-05T22:13:41Z","title":"Hierarchical Bayesian Inverse Problems: A High-Dimensional Statistics Viewpoint","version":1},"cited_work":{"arxiv_id":"2401.03074","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.03074","snapshot_observed_at":"2026-08-07T12:41:56.294901Z","title":"Hierarchical Bayesian Inverse Problems: A High-Dimensional Statistics Viewpoint","venue":"math.ST","work_id":"00039a32-29ff-43bb-8182-10489fd42b21","year":2024},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.331567Z"},"links":{"cited_paper":"/paper/2401.03074","citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:1977a240a973c721a5b48258aaab38f32f56e60cc0103932b4930b7ce080d002","observation_id":"22307ab0-afc0-4f66-9217-c4bc3871f15a","resolution":{"observed_at":"2026-08-07T12:41:56.345470Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:59.163790Z","title":null,"venue":null,"work_id":"c731941a-4a1a-4843-b642-3801e8635665","year":2024},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.371040Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:509d0c008c46f909bc21fe81de81a261bc9b339abb95197a8b1eac5a92a94500","observation_id":"2367f71c-ba6f-4b3a-94d0-af53a7f32bfc","resolution":{"observed_at":"2026-08-07T12:41:59.224151Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:58.962017Z","title":null,"venue":null,"work_id":"c9ff24e7-92fb-411c-9258-e26589485733","year":2010},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.413405Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:965219a536f66507c9b82a57e313d7c96d6e445356d805b791dfb40edd3fce7d","observation_id":"7a190366-e8fb-4033-9118-ddafd5a10059","resolution":{"observed_at":"2026-08-07T12:41:59.050347Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:58.779884Z","title":"Suuronen, N","venue":null,"work_id":"b335ede6-40e7-4a12-a6e9-37e1bac28198","year":2022},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.448858Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:40b59adac033fbfa6579ad432675bc47aec4904727dd0632ad94ba51b408da94","observation_id":"1d72b885-8aa0-4c79-81bb-542fb4f65919","resolution":{"observed_at":"2026-08-07T12:41:58.876956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:58.646130Z","title":null,"venue":null,"work_id":"2d968ec5-88a1-4034-b739-449a2b511919","year":2010},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.483288Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:9792f2885e2e0b724bbff0a5cac2dcb24a435fd878cb8eb50adde8267d6c1280","observation_id":"bc7a5086-f2d3-459a-8b9b-954d2d894256","resolution":{"observed_at":"2026-08-07T12:41:58.689607Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:58.422408Z","title":null,"venue":null,"work_id":"813fea13-09b0-4fdf-aefc-139371a27ad2","year":2001},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.523681Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:f25dd9ac9be533630fc494c670a0f0a68f3f21805e9015ded14f800be0e2641c","observation_id":"c016bc56-ddca-4538-b6b5-cbb26129a649","resolution":{"observed_at":"2026-08-07T12:41:58.525902Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:58.230527Z","title":"Uribe, J","venue":null,"work_id":"21e2d14e-090d-436d-9aef-f8291e62d820","year":2022},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.550448Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:1d8e076e2ea4554d20fb42fcbe5e370e454fc99b327895bde63db1896bc35945","observation_id":"40535191-bbb4-4292-8779-94a773ab0ca9","resolution":{"observed_at":"2026-08-07T12:41:58.300864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:58.052764Z","title":"Uribe, Y","venue":null,"work_id":"7a8fa21e-98d6-4fee-8291-bb6a0a72e302","year":2023},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.587070Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:fc290534521d17d02a02ac4aef56136aabdb9fa60082d6539bf6304a29c2ce1d","observation_id":"9823a44f-b021-4d05-9786-7c6b40072a84","resolution":{"observed_at":"2026-08-07T12:41:58.156236Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:57.870624Z","title":"Vehtari, A","venue":null,"work_id":"50daa10c-6108-420d-8c04-2b549dee1df0","year":2021},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.702767Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:16cc52fce9181838b737ab83d8735c1ce2641b953eea20a833e33c273bba3130","observation_id":"0ab8f950-cdce-4b70-a87a-1af51c9c4a3e","resolution":{"observed_at":"2026-08-07T12:41:57.968226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:57.727802Z","title":"Villani, Optimal Transport: Old and New , vol","venue":null,"work_id":"e762f6d0-c928-4bb3-9ef4-33550b180918","year":2009},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.751350Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:ab9cff65f1d0842e05d045ca3cf5e6bf5beb81547b74a9fd4d61b046d8490769","observation_id":"d44d3d0d-8208-4ebb-872b-e2a4c371502a","resolution":{"observed_at":"2026-08-07T12:41:57.785530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:57.562310Z","title":"W ang, J","venue":null,"work_id":"90a8edf9-1c8a-4626-8d0f-88bbe714d945","year":2017},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.805218Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:2ec3621a3a50e9a73f6aec9a54118a1fb4876522f0281177c471aa1aba35ff95","observation_id":"1c122f13-3668-45c0-9103-c8e8be3ff8fb","resolution":{"observed_at":"2026-08-07T12:41:57.624313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:57.400155Z","title":"West, On scale mixtures of normal distributions , Biometrika, 74 (1987), pp","venue":null,"work_id":"8b1f59a4-5968-4b01-a625-28315cea85be","year":1987},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.867122Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:d685864f95be6fc79a8c95d13e9a007dfa6fb6d504862ad81fdd3c53353a0875","observation_id":"324a2d42-8b44-4179-b68b-9f18638856a1","resolution":{"observed_at":"2026-08-07T12:41:57.469160Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:57.211528Z","title":null,"venue":null,"work_id":"5cca3d95-cec7-4807-913f-d1cc2f8a3f27","year":2004},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.924222Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:b9583d85d365ab308ecee51f99640b71e46bb387146e616bd544fd7c3bfab74d","observation_id":"3f704e21-c0e2-48dc-b24f-0ff178b6024f","resolution":{"observed_at":"2026-08-07T12:41:57.288059Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:57.054353Z","title":"Wolff and A","venue":null,"work_id":"ed54ab86-2e94-4f28-90b5-87377b25f0da","year":2004},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:55.983613Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:27316262db22f979ed6c260ef3f574c9f2be57856c24a0de686179e9f2378632","observation_id":"07bc2838-3f9b-4bc9-b6b6-92a5c6940f0b","resolution":{"observed_at":"2026-08-07T12:41:57.123600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:56.923706Z","title":"Xiao and J","venue":null,"work_id":"d9bb8632-7c36-45a1-84ff-29bd6ffad101","year":2023},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:56.086349Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:255c169debb67980a097825b3e0692f54926dfe296563b7f1fc573dc49e346de","observation_id":"e8e9b64c-7d11-4fa8-a43e-3998df58fe12","resolution":{"observed_at":"2026-08-07T12:41:56.984227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:56.771631Z","title":null,"venue":null,"work_id":"2f533d06-07f3-49f3-9eaf-31f1f43138bd","year":2020},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:56.136038Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:1513768cb38aa4aaec2b02521fec1d3fbad8d205a5d0f07000e6d577f681d7f7","observation_id":"75e72d49-d70a-4c1d-89c2-2c5b4f0faf46","resolution":{"observed_at":"2026-08-07T12:41:56.846248Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:41:56.628877Z","title":null,"venue":null,"work_id":"59cb6d72-6bee-44a7-a358-fd10a4ac961a","year":2022},"citing_paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:56.198062Z"},"links":{"citing_paper":"/paper/2505.23753"},"observation_digest":"sha256:ea54d381e987b7ffc9df252441aff26e37fcf5a337041262660d8e3b29239b38","observation_id":"55fa7d77-b65d-4029-987e-e421a5c6da4b","resolution":{"observed_at":"2026-08-07T12:41:56.690216Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.23753","last_updated":"2026-07-11T13:59:47Z","latest_version":2,"primary_category":"math.NA","snapshot_observed_at":"2026-08-07T15:27:04.441159Z","submitted_at":"2025-05-29T17:59:39Z","title":"Efficient sampling for sparse Bayesian learning using hierarchical prior normalization"},"reference_resolution":{"displayed":84,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":30,"verified_exact":1,"verified_fuzzy":53},"total_outbound_references":84},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 1 inbound Pith citation observation for arXiv:2505.23753."}