{"as_of":"2026-08-13T11:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6c345e25f16b079056bbd13a65a790721a921b6e278c59e06e624b3f6a52179c","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T17:18:07.107064Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.09183/citation-record","integrity":"/paper/2412.09183/integrity","json":"/paper/2412.09183/citation-record.json","paper":"/paper/2412.09183"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1910.06403","last_updated":"2020-12-08T19:31:38Z","snapshot_observed_at":"2026-08-08T00:58:02.525456Z","submitted_at":"2019-10-14T20:11:30Z","title":"BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.06403","snapshot_observed_at":"2026-08-11T17:18:06.942605Z","title":"Jiang, Samuel Daulton, Benjamin Letham, An- drew Gordon Wilson, and Eytan Bakshy","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.942605Z"},"links":{"cited_paper":"/paper/1910.06403","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:698f8c1f270ebd55e64cfca84f39c1fc74af7709356bb4f9f9adc5b9315e5694","observation_id":"7eeff0f9-2487-408c-ae22-07a3d13fcf69","resolution":{"observed_at":"2026-08-11T17:18:06.942605Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1511.06349","last_updated":"2016-05-12T20:51:23Z","snapshot_observed_at":"2026-08-05T16:42:28.278134Z","submitted_at":"2015-11-19T20:38:45Z","title":"Generating Sentences from a Continuous Space","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.06349","snapshot_observed_at":"2026-08-11T17:18:06.949011Z","title":"Bowman, Luke Vilnis, Oriol Vinyals, Andrew M","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.949011Z"},"links":{"cited_paper":"/paper/1511.06349","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:43fcb7f3d9e32233a7d83f7956143934a111b707eb2ae52abfdfc608c4d6316e","observation_id":"c2e899c1-2fa3-442a-8a4b-90c6f67cf9bb","resolution":{"observed_at":"2026-08-11T17:18:06.949011Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.03599","last_updated":"2018-04-10T15:48:18Z","snapshot_observed_at":"2026-08-10T09:51:06.522866Z","submitted_at":"2018-04-10T15:48:18Z","title":"Understanding disentangling in $\\beta$-VAE","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.03599","snapshot_observed_at":"2026-08-11T17:18:06.955163Z","title":"Burgess, Irina Higgins, Arka Pal, Loic Matthey, Nick Watters, Guillaume Desjardins, and Alexander Lerchner","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.955163Z"},"links":{"cited_paper":"/paper/1804.03599","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:bfbb514a7f405c7009d265d252491bbd7a7e34e4b05415c21926f705b34dcb1e","observation_id":"a1756b0a-9322-4d2d-9158-d2772740c1a9","resolution":{"observed_at":"2026-08-11T17:18:06.955163Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.09673","last_updated":"2020-03-21T14:45:43Z","snapshot_observed_at":"2026-08-13T06:13:37.427854Z","submitted_at":"2020-03-21T14:45:43Z","title":"A dimensionality reduction technique for unconstrained global optimization of functions with low effective dimensionality","version":1},"cited_work":{"arxiv_id":"2003.09673","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.09673","snapshot_observed_at":"2026-08-11T17:18:07.522791Z","title":"A dimensionality reduction technique for unconstrained global optimization of functions with low effective dimensionality","venue":"math.OC","work_id":"a9631fa8-97f5-404a-b56e-4cb6c2491cca","year":2020},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.961223Z"},"links":{"cited_paper":"/paper/2003.09673","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:acc981ff2065403ba3659c6b0fcebd9d32bc86d768e03eba6cef65ab21f3e94f","observation_id":"67407462-ef89-4433-891d-a35f767efafa","resolution":{"observed_at":"2026-08-11T17:18:07.528877Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.12102","last_updated":"2021-07-26T10:45:49Z","snapshot_observed_at":"2026-08-13T08:21:24.278014Z","submitted_at":"2021-07-26T10:45:49Z","title":"Global optimization using random embeddings","version":1},"cited_work":{"arxiv_id":"2107.12102","doi":null,"metadata_source":"pith","pith_arxiv_id":"2107.12102","snapshot_observed_at":"2026-08-11T17:18:07.499247Z","title":"Global optimization using random embeddings","venue":"math.OC","work_id":"7b20ef85-6470-4109-915d-271051074c22","year":2021},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.967277Z"},"links":{"cited_paper":"/paper/2107.12102","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:49259dce3095243cb917a297a844aaf8f0022fdc1b1ca31105923050eecd18de","observation_id":"73522148-20d7-4959-b9d1-7bfa353e7bf2","resolution":{"observed_at":"2026-08-11T17:18:07.504687Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T17:18:06.972607Z","title":"Escaping local minima with local derivative-free methods: a numerical investigation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.972607Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:9887507827a8e7190b6bb3cbdcc693f7bee2a2047ea0057439e289d3f331b84d","observation_id":"e0dcd17d-5027-4b6f-987d-7844d0214111","resolution":{"observed_at":"2026-08-11T17:18:06.972607Z","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":"2026-08-11T17:18:07.799372Z","title":"Optimization resources: A collec- tion of software and resources for nonlinear optimization","venue":null,"work_id":"61b51154-ed68-4285-b346-c7e1365bc39e","year":null},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.978321Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:834e58cf2b176fb8904eef98222f7d5afd005140c03d1a4aabed113e1ce4ecf3","observation_id":"7f2fe348-2a36-4a0d-9415-7b316c3c1a9e","resolution":{"observed_at":"2026-08-11T17:18:07.805220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.05908","last_updated":"2021-01-03T16:56:46Z","snapshot_observed_at":"2026-08-10T10:13:44.536180Z","submitted_at":"2016-06-19T21:02:30Z","title":"Tutorial on Variational Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.05908","snapshot_observed_at":"2026-08-11T17:18:06.983925Z","title":"Tutorial on variational autoencoders, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.983925Z"},"links":{"cited_paper":"/paper/1606.05908","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:fc61d15f0e3d8162b1ad8c14e223efaced1ac13568fe207f8f9dc41dd734235f","observation_id":"4e308fff-0c88-486c-a316-08666cd93da3","resolution":{"observed_at":"2026-08-11T17:18:06.983925Z","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":"2026-08-11T17:18:07.782385Z","title":"Ernesto and U.P","venue":null,"work_id":"86eb1f9f-ceb0-4cfc-8db7-af28ec40b47f","year":2005},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.990729Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:a53a98ce7418dd0d6d33a9b9304255e19a0372e28be0188d8ad5e74062e83d00","observation_id":"d60eae57-0754-4eb2-9de2-5a21b3fd6129","resolution":{"observed_at":"2026-08-11T17:18:07.787552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.02811","last_updated":"2018-07-08T13:06:26Z","snapshot_observed_at":"2026-08-07T12:49:05.688504Z","submitted_at":"2018-07-08T13:06:26Z","title":"A Tutorial on Bayesian Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.02811","snapshot_observed_at":"2026-08-11T17:18:06.995869Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:06.995869Z"},"links":{"cited_paper":"/paper/1807.02811","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:1f651de0d1bb1c7c0d65984392fac3abae3335cdbacd0fb940927590f2c7be52","observation_id":"0262b64d-fb93-4f20-aca6-840e3746ea63","resolution":{"observed_at":"2026-08-11T17:18:06.995869Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.10145","last_updated":"2019-06-10T21:43:02Z","snapshot_observed_at":"2026-08-07T15:27:18.042416Z","submitted_at":"2019-03-25T06:28:24Z","title":"Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.10145","snapshot_observed_at":"2026-08-11T17:18:07.001542Z","title":"Cyclical annealing schedule: A simple approach to mitigating kl vanishing, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.001542Z"},"links":{"cited_paper":"/paper/1903.10145","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:9175c3d8410ef5e89938fce7800a87a705345481e28cc1757ade1a142589b46c","observation_id":"5fa1812f-e5e1-4fd5-9e0a-1b220fba37ad","resolution":{"observed_at":"2026-08-11T17:18:07.001542Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.03609","last_updated":"2021-11-01T11:53:58Z","snapshot_observed_at":"2026-08-05T00:36:17.087265Z","submitted_at":"2021-06-07T13:35:47Z","title":"High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.03609","snapshot_observed_at":"2026-08-11T17:18:07.007906Z","title":"Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, and Haitham Bou-Ammar","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.007906Z"},"links":{"cited_paper":"/paper/2106.03609","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:14806036116be6b87727577162b263a0d89e32310754dc1b0e699785f661c9e3","observation_id":"04386cb1-a431-411e-8d1c-201f480448c9","resolution":{"observed_at":"2026-08-11T17:18:07.007906Z","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":"2026-08-11T17:18:07.766192Z","title":null,"venue":null,"work_id":"f7bef07f-7181-4d29-98fd-299d8747a2e6","year":1993},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.014145Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:d686e94ed85b57d32ea5ee92e8aee178d5aa2cad1e1802fce2007172c74caa02","observation_id":"248090a7-edb4-42c8-a027-3796878cc07c","resolution":{"observed_at":"2026-08-11T17:18:07.771098Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T17:18:07.750099Z","title":"Deep metric learning using triplet network","venue":null,"work_id":"fc13b999-55dd-4781-99d1-8dc6e7dc3ba5","year":2015},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.019432Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:2559a217cbbfe232ddcab418476a3282aad4b530bdf176c169948a57c478b1f5","observation_id":"8f4d3c78-ca9e-4eea-b339-bc56f56ad582","resolution":{"observed_at":"2026-08-11T17:18:07.754995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02229","last_updated":"2024-12-12T09:53:38Z","snapshot_observed_at":"2026-08-13T04:27:40.646807Z","submitted_at":"2024-02-03T18:19:46Z","title":"Vanilla Bayesian Optimization Performs Great in High Dimensions","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02229","snapshot_observed_at":"2026-08-11T17:18:07.024672Z","title":"Vanilla bayesian optimization performs great in high dimensions, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.024672Z"},"links":{"cited_paper":"/paper/2402.02229","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:055050172942e5c8bc50af7352c8ea4490234b3b7389f478cfc1af0e93a14ff5","observation_id":"a92ae9e2-a8c3-4126-9f24-9b3d94f13f1c","resolution":{"observed_at":"2026-08-11T17:18:07.024672Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.04403","last_updated":"2023-02-08T15:25:57Z","snapshot_observed_at":"2026-08-12T20:09:27.350689Z","submitted_at":"2018-02-13T00:05:19Z","title":"TVAE: Triplet-Based Variational Autoencoder using Metric Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.04403","snapshot_observed_at":"2026-08-11T17:18:07.029390Z","title":"Tvae: Triplet-based variational autoencoder using metric learning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.029390Z"},"links":{"cited_paper":"/paper/1802.04403","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:fe71406215c64373aae90cbeddd00c6d390ce813cf54674a1e7bf5a18bf82e23","observation_id":"a7b24f17-b7e6-4e65-9152-77ef9b729b49","resolution":{"observed_at":"2026-08-11T17:18:07.029390Z","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":"2026-08-11T17:18:07.735496Z","title":null,"venue":null,"work_id":"8fbd33bb-561f-4e8a-889c-a2adc3e3bf9b","year":1998},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.035069Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:224aa10438a47bc85047ed9360a826520ac7f375a097e0df8f4f96f8eeed52cf","observation_id":"60ca4c45-3a57-41f2-9d15-be6838c93829","resolution":{"observed_at":"2026-08-11T17:18:07.740117Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-11T17:18:07.039473Z","title":"Kingma and Jimmy Ba","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.039473Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:36e6a45bbde15bd06e983946e409dc4c34db3f6893c590a6544b6da8a3c7e32b","observation_id":"7b4f5246-3704-4df1-9515-1375a593f382","resolution":{"observed_at":"2026-08-11T17:18:07.039473Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6114","last_updated":"2022-12-10T21:04:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-12-20T20:58:10Z","title":"Auto-Encoding Variational Bayes","version":11},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6114","snapshot_observed_at":"2026-08-11T17:18:07.044266Z","title":"Auto-encoding variational bayes, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.044266Z"},"links":{"cited_paper":"/paper/1312.6114","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:7a06eabdd7a9c16968b365f085a6e80883cc7ba4490499c2f2da86f80645c711","observation_id":"ab7b3589-e0ac-450a-a1fb-47dab8a51db6","resolution":{"observed_at":"2026-08-11T17:18:07.044266Z","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":"2026-08-11T17:18:07.718371Z","title":null,"venue":null,"work_id":"738b88c9-c33a-4774-96dd-8089a5087897","year":2009},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.048664Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:5e04d4cf61ea2e64e61454f5ffc1cd75701326b2dfd3bdca354bdbbb0e35a1ec","observation_id":"9e3a24bb-edbe-4e2e-bb6b-a62f896bb98e","resolution":{"observed_at":"2026-08-11T17:18:07.724143Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T17:18:07.701678Z","title":"A framework for bayesian opti- mization in embedded subspaces","venue":null,"work_id":"ed42abe0-cef3-40bd-938f-d7bd097cb2ba","year":2019},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.053008Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:56b4d4ce51d01e71736b98a9261052eb3a30530fdc6a64888044a2e8d9826207","observation_id":"8d7d9026-514d-426c-a582-be98036bc620","resolution":{"observed_at":"2026-08-11T17:18:07.707246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.13997","last_updated":"2021-10-29T15:42:08Z","snapshot_observed_at":"2026-07-06T10:08:49.711870Z","submitted_at":"2020-10-27T02:15:15Z","title":"A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance","version":3},"cited_work":{"arxiv_id":"2010.13997","doi":null,"metadata_source":"pith","pith_arxiv_id":"2010.13997","snapshot_observed_at":"2026-08-11T17:18:07.206048Z","title":"A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance","venue":"stat.ML","work_id":"5ac98eae-367c-49f7-8117-9f3ea4f90e85","year":2020},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.058767Z"},"links":{"cited_paper":"/paper/2010.13997","citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:81742c772070420e7a10be3c572c97aa489c2304a879143edf407e6c17462c93","observation_id":"f066d117-d56e-4017-b32b-a766e3146ccc","resolution":{"observed_at":"2026-08-11T17:18:07.211158Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1108/02644400210430190","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T17:18:07.180112Z","title":"On the robustness of a simple domain reduction scheme for simulation-based optimization","venue":null,"work_id":"80db1975-c481-49a7-8b17-7c7e99a8fb5c","year":2002},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.064485Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:6e675fa5c554e74415998223628c97e6026d8a393d15f6d9428be83bd47bea15","observation_id":"a4ba31ba-d924-4e3c-91dc-07c18c06c77d","resolution":{"observed_at":"2026-08-11T17:18:07.186359Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T17:18:07.683596Z","title":"Surjanovic and D","venue":null,"work_id":"fec8f54c-80cd-43d2-b29b-0730f18c8689","year":2013},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.069441Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:962c8915ff5f42a766d2df99d3dc345363733591973568915239fb69399690ab","observation_id":"4d922604-54af-47da-a15d-2a43b7986ab2","resolution":{"observed_at":"2026-08-11T17:18:07.689194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T17:18:07.664451Z","title":"Sample-efficient opti- mization in the latent space of deep generative models via weighted retraining","venue":null,"work_id":"3b9e0fae-aaa5-41ac-9741-4d7e44f106c7","year":2020},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.075380Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:eb877bdedeaf5d40e7167c4568051077270cd53b18dace07d184653ba869da99","observation_id":"6fdb5a1c-8f8b-464d-b272-527886b11564","resolution":{"observed_at":"2026-08-11T17:18:07.670720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.procs.2020.01.079","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T17:18:07.162357Z","title":"Velliangiri, S","venue":null,"work_id":"2d9ebd97-f0ed-40bb-acf6-99d83d44e893","year":2019},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.080195Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:8f3dee2d3c569f5b49d349f1b87be1ec7a45c94566a9cc200ddca5fd29f1f716","observation_id":"31f96cdd-290c-42fb-a14f-4f8c1c736bd2","resolution":{"observed_at":"2026-08-11T17:18:07.168286Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T17:18:07.647479Z","title":null,"venue":null,"work_id":"4e24d493-5023-4854-b529-97904c0d87ac","year":2013},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.085434Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:93dfe20567cb8f3d9c1996968dfb1df427aaaf97d3cccdd51cb88f8aa7730801","observation_id":"38efd49b-e121-4d4c-8fc8-9c65a3e650ca","resolution":{"observed_at":"2026-08-11T17:18:07.653042Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T17:18:07.629602Z","title":"Black, and Eric Nyberg","venue":null,"work_id":"c5dab1ec-54d9-4930-a8d5-51060dcbabd6","year":2019},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.090429Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:f7b4d1675033dc6e84efb4fdb6f453141379bffae77d5caad9a71439a12305ee","observation_id":"74eec4d3-4d5f-4ca6-8a85-bea3af0cd77a","resolution":{"observed_at":"2026-08-11T17:18:07.635864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T17:18:07.611890Z","title":"The models are pre-trained according to the details in Table 5","venue":null,"work_id":"b2736695-48cd-4b26-a119-2e9d75b500ff","year":null},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.101612Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:aa57dd57fb108b66dac96dc206329ccf1cf6e030bc7b2484e3cb3e4b5446dee5","observation_id":"ac6aad8a-b722-45cc-b60e-c751c9b5b07a","resolution":{"observed_at":"2026-08-11T17:18:07.617665Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T17:18:07.596302Z","title":null,"venue":null,"work_id":"f9415905-2aa1-44f4-80d9-f5a6a6051a8b","year":null},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.107064Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:de169fe8fc3d2475eabd729521a3463f721b3f77d21516a65b9032be446782df","observation_id":"89dd4d0d-233c-4129-86b3-459db2e73262","resolution":{"observed_at":"2026-08-11T17:18:07.600985Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.21437/interspeech.2019-2278","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T17:18:07.143791Z","title":"URL http://dx.doi.org/10.21437/ Interspeech.2019-2278","venue":null,"work_id":"f0129983-44d1-4b69-bf78-6acc6a0ac56a","year":2019},"citing_paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-11T17:18:07.095854Z"},"links":{"citing_paper":"/paper/2412.09183"},"observation_digest":"sha256:f3ac9caf6db9a5159f045cd2785239705aeb7767624a34064ed9789a585e445b","observation_id":"17f46729-f93e-41c7-8f3b-89c04496c7af","resolution":{"observed_at":"2026-08-11T17:18:07.150325Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.09183","last_updated":"2024-12-12T11:27:27Z","latest_version":1,"primary_category":"math.OC","snapshot_observed_at":"2026-08-13T04:10:25.472801Z","submitted_at":"2024-12-12T11:27:27Z","title":"Dimensionality Reduction Techniques for Global Bayesian Optimisation"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":6,"verified_fuzzy":8},"total_outbound_references":31},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2412.09183."}