{"as_of":"2026-08-11T04:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:664028686c5da79a9f09478e791361183d8a5b3fbc77e51d477db10dab3b8845","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T16:36:50.900513Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2502.06165/citation-record","integrity":"/paper/2502.06165/integrity","json":"/paper/2502.06165/citation-record.json","paper":"/paper/2502.06165"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:36:51.851612Z","title":"Importance sampling: Intrinsic dimension and computational cost","venue":null,"work_id":"4ab3b5bd-9141-441e-a6d8-d5b9067657ea","year":2017},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.613065Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:7c9cc57ac7b5dc7002744de41478ff3e4c542848c595392cad025cc43faa4adc","observation_id":"a2effe28-7f85-414c-8990-e13703b2c11d","resolution":{"observed_at":"2026-08-08T16:36:51.856374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.836448Z","title":"Empirical processes associated with v-statistics and a class of estimators under random censoring","venue":null,"work_id":"090c53b7-d1de-4a92-848d-352629ea958b","year":1986},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.618547Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:0bf0fdd49f1c5efe8956f694a7d558a2337878c4430a1256617d3f9e0510670d","observation_id":"2dff8d60-960a-4a7f-b153-a44d37d7a338","resolution":{"observed_at":"2026-08-08T16:36:51.841311Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.821708Z","title":"Kernels for vector-valued functions: A review","venue":null,"work_id":"a122bf81-4c8a-49ca-90f3-52f9c119c082","year":2012},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.623564Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:11272b803c45a7729ea98b4002df64adafec486c7f178b16690dd22239e6de0e","observation_id":"a24924a0-4933-44d9-bbf9-292e245d4632","resolution":{"observed_at":"2026-08-08T16:36:51.826450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.807021Z","title":"An ensemble adjustment kalman filter for data assimilation","venue":null,"work_id":"6b4c34d9-8a13-47df-b08d-7ca2a27275ec","year":2001},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.629101Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:df0615deab38e347ea301d6edc817238195e83190e8cd3d0873938c253c16886","observation_id":"75d4d474-43f2-4185-aff1-9421ea1926b6","resolution":{"observed_at":"2026-08-08T16:36:51.811947Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.791265Z","title":"An adaptive covariance inflation error correction algorithm for ensemble filters","venue":null,"work_id":"ef738ac5-ede7-44a4-bd16-1714ee908f8a","year":2007},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.634051Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:745898d0d20b4a6a9a1d022cd2a7bb79c0305e4578b82a6e083020bd73414377","observation_id":"27a1b008-8b5b-41d8-a600-946ed4ad4c13","resolution":{"observed_at":"2026-08-08T16:36:51.796119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.776645Z","title":"A non-gaussian ensemble filter update for data assimilation","venue":null,"work_id":"a930dddc-bfc9-4fd5-aa9e-435cd8f2312c","year":2010},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.638837Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:fe07420d7e347a613a5a5d7b5606e77db6b23f84db8d76b7f4f945d2e670d668","observation_id":"877d7fb3-0d92-495f-996f-c65cec82a16f","resolution":{"observed_at":"2026-08-08T16:36:51.781393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.761282Z","title":"Wasserstein generative adversarial networks","venue":null,"work_id":"8b700b1a-f244-4c73-ad62-6622d2160f6d","year":2017},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.643884Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:2a68171380d1399b6f8ec0b756720fa6ef75b29b9c09667cc6e16012ecab7a41","observation_id":"3a99cfa2-aed2-4698-aca3-33db9d4ac79c","resolution":{"observed_at":"2026-08-08T16:36:51.766364Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.745981Z","title":"A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking","venue":null,"work_id":"130beaf6-bed2-46a6-82f3-ece278b60780","year":2002},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.648275Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:fe2540baa4667cddd9a4f0b807674fcb96f0b6d7339a2247a9842ad664febbb9","observation_id":"e61f3039-a0bd-4179-bf6b-1e8fe05b16f4","resolution":{"observed_at":"2026-08-08T16:36:51.750963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.729730Z","title":"Sequential data assimilation techniques in oceanography","venue":null,"work_id":"8ddf2b46-fd47-49db-bfaa-0003f388c8f7","year":2003},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.652886Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:43dcb90bb8aebbd519fe510b5b30a0f207d101e15d3569e2de955a5d3f2c9a23","observation_id":"fabd71fe-a04c-4e1b-9632-55e64b3ccaeb","resolution":{"observed_at":"2026-08-08T16:36:51.735108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.712793Z","title":"Adaptive sampling with the ensemble transform kalman filter","venue":null,"work_id":"0c7490a9-4a07-4f17-9376-00a6c34677ff","year":2001},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.657370Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:8f333b6f71813a8b029933c64d5bd5fa96c18da2414e278be25a796914142462","observation_id":"1f628c66-a6ab-4136-83b0-894a51b1fb02","resolution":{"observed_at":"2026-08-08T16:36:51.717886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.697484Z","title":null,"venue":null,"work_id":"5ba085b9-efcd-419c-81c3-f02ff36edd2b","year":1992},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.661745Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:63c089e4a54b1101a4be07f5ed70e5847b851d9ce7925dff9568670eb132aa08","observation_id":"54f95027-cf31-4210-afe9-710c58808275","resolution":{"observed_at":"2026-08-08T16:36:51.702210Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.15801","last_updated":"2025-07-16T14:47:13Z","snapshot_observed_at":"2026-07-06T17:21:34.093816Z","submitted_at":"2024-01-28T23:18:10Z","title":"On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension","version":2},"cited_work":{"arxiv_id":"2401.15801","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.15801","snapshot_observed_at":"2026-08-08T16:36:50.999405Z","title":"On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension","venue":"stat.ML","work_id":"e753b555-fbcf-473e-92bb-04214b2d7c58","year":2024},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.666423Z"},"links":{"cited_paper":"/paper/2401.15801","citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:df1b50669bec12d32a595378359ec1735aa46514ced6441bb38f46f307a8c350","observation_id":"aca19297-26de-4137-9c1b-d542186ea7a6","resolution":{"observed_at":"2026-08-08T16:36:51.007095Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.681977Z","title":"Sequential data assimilation with a nonlinear quasi-geostrophic model using monte carlo methods to forecast error statistics","venue":null,"work_id":"446ae9eb-061a-40dd-bbf6-67407690d590","year":1994},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.671613Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:9cd5a2da8874e77d1b34b3bb748fe31bf66c8f936b43b18a4462bf0233442654","observation_id":"a225e30c-228a-4bee-8fc2-e5bcf031e283","resolution":{"observed_at":"2026-08-08T16:36:51.687199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.666441Z","title":"The ensemble kalman filter: Theoretical formulation and practical implementation","venue":null,"work_id":"ad41e38b-2545-4728-b4c0-d9284db27f06","year":2003},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.676296Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:ea5577f571b6db53457c34cdc10f85fdcd740b41ffd88aa447e5111a3d883276","observation_id":"11b2dfce-dab7-4637-b13d-6521ab0c5a8c","resolution":{"observed_at":"2026-08-08T16:36:51.671515Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.02424","last_updated":"2022-07-24T20:51:10Z","snapshot_observed_at":"2026-08-10T23:52:50.094020Z","submitted_at":"2021-12-04T20:27:31Z","title":"Variational Wasserstein gradient flow","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.02424","snapshot_observed_at":"2026-08-08T16:36:50.680883Z","title":"Variational wasserstein gradient flow","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.680883Z"},"links":{"cited_paper":"/paper/2112.02424","citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:75b96e1f3e5b7b2f016e2e7a6953d27333e568ffa6e630c7e9683de967656baf","observation_id":"6d782784-2554-4db8-9ea9-97515a455382","resolution":{"observed_at":"2026-08-08T16:36:50.680883Z","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":"2026-08-08T16:36:51.651053Z","title":"Data assimilation for the geosciences: From theory to application","venue":null,"work_id":"d29ad106-5cda-4b35-bb94-c31dc299a2a2","year":2022},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.685838Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:22145d55d061bdae939125e293e5891a6e5c533d21ee51f1ee0ac368aeff9cb5","observation_id":"7612a85a-450c-4c20-8f85-c21037bb52c9","resolution":{"observed_at":"2026-08-08T16:36:51.655986Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:50.690458Z","title":"Covariance tapering for interpolation of large spatial datasets","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.690458Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:f946fedd5bbf782cd81d8b52c8dcd9fc260e74a5a3e265d2535e5a1c2001481b","observation_id":"ad2e29cc-d1f8-46bc-841e-5bebb85ee5db","resolution":{"observed_at":"2026-08-08T16:36:50.690458Z","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":"2026-08-08T16:36:51.625873Z","title":"Gamerman","venue":null,"work_id":"82f71c9b-63e2-4dfa-b954-2bfd99f1f655","year":1998},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.695109Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:1f6a45325435d9cf0706f28356a298228787446e8e0fd96a96d3c7d8fa9ed40c","observation_id":"7897f824-597f-4ef1-8516-f2244f88983a","resolution":{"observed_at":"2026-08-08T16:36:51.630611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.610287Z","title":null,"venue":null,"work_id":"4f8838b5-bca1-4566-a987-a1322c305ab9","year":1991},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.699801Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:c396f06302f7ce810ee39b31cfd0ec0821396c5601d4c2f7583f0d15eb3cd730","observation_id":"7c42aaa6-d007-4094-957e-664f188b856f","resolution":{"observed_at":"2026-08-08T16:36:51.615316Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:50.704849Z","title":"Generative adversarial nets","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.704849Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:8d071e9ed83fe5cf901f81f2f503f8db2328ac92545ebc706105706e0588917f","observation_id":"fea7cb6e-81fa-423a-8656-83455c19adda","resolution":{"observed_at":"2026-08-08T16:36:50.704849Z","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":"2026-08-08T16:36:51.584386Z","title":"Novel approach to nonlinear/non-gaussian bayesian state estimation","venue":null,"work_id":"dfefe458-9d6f-4fb8-8cf6-cb3c5a72700b","year":1993},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.709616Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:7b2d941182b61da0d07c3b39b1f529346b0db136ab0c3aec93630920f51230a3","observation_id":"2f49ec7b-b975-4435-915f-cc2dfeb9fa1a","resolution":{"observed_at":"2026-08-08T16:36:51.589415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.568736Z","title":"A Distribution-Free Theory of Nonparametric Regression","venue":null,"work_id":"7895c08d-385e-419c-8910-b30a46210596","year":2002},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.714819Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:7eb4e91cd1375759ab6de546a9d79b6905b78c6b5bf12b63b08329d004d14c41","observation_id":"0f97720b-8379-47ea-973d-ebf613581363","resolution":{"observed_at":"2026-08-08T16:36:51.573591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.552624Z","title":"Advances in importance sampling","venue":null,"work_id":"5d9bc099-1170-44d0-a9c5-9386d1c5a2ec","year":1988},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.719525Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:655ab145415c25a6c1150d1fb0a435659915f80d07f15b1bac839056393d7004","observation_id":"e1dc51c3-751f-419d-a469-9eedd98d87e2","resolution":{"observed_at":"2026-08-08T16:36:51.557492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.536501Z","title":"Efficient data assimilation for spatiotemporal chaos: A local ensemble transform kalman filter","venue":null,"work_id":"595f6a94-e3fd-4a40-9aa1-7baf22183932","year":2007},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.724376Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:0f4553f35e2e1e9c1da40fc94eec49551d54d08e3ffc7a10e4c697bc0a4b93ee","observation_id":"109f6621-fb48-4f25-b067-5247b64cede6","resolution":{"observed_at":"2026-08-08T16:36:51.541442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:50.728979Z","title":"The variational formulation of the fokker--planck equation","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.728979Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:3e29e55dee576b332eda0a62427f8e31d73987380fa6cfc8105942150617f156","observation_id":"32c8933e-d282-430e-bfd0-88135a4a97de","resolution":{"observed_at":"2026-08-08T16:36:50.728979Z","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":"2026-08-08T16:36:51.511107Z","title":null,"venue":null,"work_id":"898d2a84-ce12-498a-aeae-0d2ed58d1fcf","year":1960},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.733439Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:7a02bcc922b2da4a3c27f962b7502702faf3de1df34ca181edef04d8e17ff558","observation_id":"892e3a53-c730-42dd-b83b-b2c3c0a89aab","resolution":{"observed_at":"2026-08-08T16:36:51.515758Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.496202Z","title":"Understanding the ensemble kalman filter","venue":null,"work_id":"de4e6c50-be08-48bd-b9c4-f3217f374de1","year":2016},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.737866Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:162899536cfbe52f1a5e2aad0dfec7b39190bd7266609e73d50f9429a5502f98","observation_id":"496d37db-1f7d-436c-9ec0-43af6ca70757","resolution":{"observed_at":"2026-08-08T16:36:51.501100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.480451Z","title":"Ensemble kalman methods for high-dimensional hierarchical dynamic space-time models","venue":null,"work_id":"a245a1fb-d493-4a19-a400-920155953272","year":2020},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.742637Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:30777ac3d04a0fe352999bde39e3c276c5ce56e4096a3ba17f2b21d8133b7b13","observation_id":"e74fb63a-f574-49e1-bc0e-005a46667767","resolution":{"observed_at":"2026-08-08T16:36:51.485791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.464247Z","title":"Introduction to kalman filter and its applications","venue":null,"work_id":"0c3f8bf4-8c14-4227-ae09-06fe713be9b2","year":2018},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.747072Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:1572c0720f38cb5821ddec6eaa8b09f0ca6bd8febeaf38e1a18c0f3dea48745e","observation_id":"ea48cac6-07c8-4f9c-8a52-dc1c4c1afd32","resolution":{"observed_at":"2026-08-08T16:36:51.469553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.447191Z","title":"A note on importance sampling using standardized weights","venue":null,"work_id":"1cb5f3da-2f7a-4bf0-a9c8-7c4e860ce7a1","year":1992},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.751650Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:419c8c76beb3af70c14a735a697a137f8769fdd39eb3063323d37641b0f1b5e4","observation_id":"734c0878-9c3c-4785-9405-2d699740599d","resolution":{"observed_at":"2026-08-08T16:36:51.452773Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.431793Z","title":"Recursive monte carlo filters: algorithms and theoretical analysis","venue":null,"work_id":"57eb8556-891c-4780-9134-5f5222322dbc","year":1983},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.756236Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:db48d5482921d0903d74224cd1f7d56927b9adefaceedda7e9c4e4b225c05c4f","observation_id":"ee48f7ac-10ee-411e-bb83-9e58aac4a7d9","resolution":{"observed_at":"2026-08-08T16:36:51.436553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.415621Z","title":"Bellman filtering and smoothing for state--space models","venue":null,"work_id":"603a2873-21ac-4253-a641-ac9686f1d344","year":2024},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.760595Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:33a7103c1efc87a6a30bf8656a0147b40afdb47c82fc368cbebc26ff6f43ae41","observation_id":"49f520df-6e71-42b9-bd51-766e0ec7df49","resolution":{"observed_at":"2026-08-08T16:36:51.421075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.400403Z","title":"A moment matching ensemble filter for nonlinear non-gaussian data assimilation","venue":null,"work_id":"3c43bb5b-ceb3-4ee1-8c4d-ea251b6c9649","year":2011},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.765189Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:4f12a14d5d31ef4c4131c358ee13a1089d0cf853b9406db872be2450ef333c62","observation_id":"1f3445cd-47c5-42f9-a54f-f8d8e6d665f2","resolution":{"observed_at":"2026-08-08T16:36:51.405353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.384850Z","title":"How well generative adversarial networks learn distributions","venue":null,"work_id":"0fe98e69-ee0f-4193-abe0-8277567e66c1","year":2021},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.769678Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:7a897693a61c0e9f672dc403b9469858a520d2598cb303800762b6041fc4eeee","observation_id":"72b24ccf-e930-41f2-8c1a-7ba891d4918b","resolution":{"observed_at":"2026-08-08T16:36:51.389754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:50.774506Z","title":"Stein variational gradient descent: A general purpose bayesian inference algorithm","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.774506Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:1dfa7b6c11711eed27a8334795e36e9bdb32c6f737b51234fa9976a9fe76e6c9","observation_id":"035dfd97-9695-4fd7-93c6-471850b7e456","resolution":{"observed_at":"2026-08-08T16:36:50.774506Z","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":"2026-08-08T16:36:51.360314Z","title":"Implicit regularization in nonconvex statistical estimation: Gradient descent converges linearly for phase retrieval and matrix completion","venue":null,"work_id":"7d341a9a-2477-41e9-b739-78102b7eabdd","year":2018},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.779272Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:bacaa8a9e8f0f0cf1cd9abc67f66456c6828dc807c4cf22cf1339c4cdc0e3fe9","observation_id":"3f1c977b-91fc-41ad-9632-91643cd4d6a7","resolution":{"observed_at":"2026-08-08T16:36:51.365418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.345327Z","title":"Concentration inequalities for log-concave distributions with applications to random surface fluctuations","venue":null,"work_id":"1fde3ebd-42c4-437c-a1da-8dbd08593da2","year":2022},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.783908Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:506e4cedbaa860e58edfaa661d582d90c09f23733c1bb62435167ba59bc829f1","observation_id":"2a6ca180-78c6-4952-97ef-10a448b42fef","resolution":{"observed_at":"2026-08-08T16:36:51.350284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.330564Z","title":"Fastslam 2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges","venue":null,"work_id":"0e347db9-1f6f-4e66-994d-35ed01c4f485","year":2003},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.788165Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:0aef7745b9349f72063fcbbf20c4da20b25cad4b3ed402786daac7044c08ce44","observation_id":"d0a95539-d485-43aa-9d61-6ac61d78d5f3","resolution":{"observed_at":"2026-08-08T16:36:51.335422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.315691Z","title":"Rao-blackwellised particle filtering for dynamic bayesian networks","venue":null,"work_id":"75b4f837-05a8-4d90-af80-3d7bb626b8e4","year":2001},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.792563Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:205b94181978d346a5df11107ccf6ad13f0e528b28b410fc3800917a850794e1","observation_id":"f35d1f33-a150-4257-814f-d856b6ebc675","resolution":{"observed_at":"2026-08-08T16:36:51.320475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.300794Z","title":"Improving regularised particle filters","venue":null,"work_id":"37a2b62e-c44f-4c51-8a21-1d0fdfd13e3b","year":2001},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.796739Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:51d0e71eef6c78e93f2d7961763a0a1c8d18305eed198b3d2efd066bc52b8186","observation_id":"57db7af2-2e73-4398-9f87-6931e2be0c13","resolution":{"observed_at":"2026-08-08T16:36:51.305621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.286290Z","title":"Merging particle filter for sequential data assimilation","venue":null,"work_id":"d8c2b353-95be-4b36-9e91-2fa7e2bbb583","year":2007},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.801115Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:3e5c785782ee5e65b82108a7abcffdbd0ca8d3bdfb27c68092019f9d8369f0a0","observation_id":"a479a142-8da8-4934-ba1c-571006e03854","resolution":{"observed_at":"2026-08-08T16:36:51.290995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.271791Z","title":"Diffusion models are minimax optimal distribution estimators","venue":null,"work_id":"8026a860-16f9-41fd-b5bb-ef86d953dcd6","year":2023},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.805538Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:5f676a40682052641065ec9540ad7fee07490370942014beaa4f4f4922d02077","observation_id":"c9e41938-5a75-4797-b482-bcae75e0d81f","resolution":{"observed_at":"2026-08-08T16:36:51.276503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.256220Z","title":"Optimal approximation of piecewise smooth functions using deep relu neural networks","venue":null,"work_id":"05dff2f7-ff37-4623-90d3-8b6d573845b8","year":2018},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.809869Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:9f24634af65a64ac4e13be6ca26dd7ee49a49984c81378af893344d7c91c2f69","observation_id":"fb703fcf-5f04-4b79-9631-88992f8278ee","resolution":{"observed_at":"2026-08-08T16:36:51.261455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.240160Z","title":"A localized particle filter for high-dimensional nonlinear systems","venue":null,"work_id":"c940b637-f880-4524-87be-78d6ec497004","year":2016},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.814431Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:e237daa4c314cb22553f1a95d16f17b3274475db133b17fbf2507854e09a2a3e","observation_id":"2d842c8e-80e9-4747-8288-3098a8b7b0a7","resolution":{"observed_at":"2026-08-08T16:36:51.245182Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.225394Z","title":"Overview of global data assimilation developments in numerical weather-prediction centres","venue":null,"work_id":"7256c9d2-12d7-4d77-a381-68ec0a5c22af","year":2005},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.818589Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:969c57e9566ef9313a1ae008e634679237edd1b815c1e9b2881079fe94e997f7","observation_id":"f29d1767-32f9-4db8-83c2-1e6352b4d405","resolution":{"observed_at":"2026-08-08T16:36:51.230256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.06125","last_updated":"2022-04-13T01:10:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-13T01:10:33Z","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.06125","snapshot_observed_at":"2026-08-08T16:36:50.823081Z","title":"Hierarchical text-conditional image generation with clip latents","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.823081Z"},"links":{"cited_paper":"/paper/2204.06125","citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:0dbb49781128583c258812b6c05b435713998bdfedc379cca3bc343efc943ca4","observation_id":"a5339959-67a4-4c2a-bab1-2f93c16b5fc8","resolution":{"observed_at":"2026-08-08T16:36:50.823081Z","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":"2026-08-08T16:36:51.209800Z","title":"A nonparametric ensemble transform method for bayesian inference","venue":null,"work_id":"c543d755-a494-4e7c-9cf0-ad84beb9c871","year":2013},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.828038Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:bdbba9b07b6d99a7a8633d96f0bd8184cf2caa3e0fbe8530894b4d4aa434feae","observation_id":"4d22b2b2-0d18-412b-88df-45664f1db368","resolution":{"observed_at":"2026-08-08T16:36:51.214851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.193424Z","title":"Venezuelan rainfall data analysed by using a bayesian space--time model","venue":null,"work_id":"8a9dddb6-5742-4c65-b3f8-162a9a15644a","year":1999},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.832663Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:a370139cac30a20d5786b282bba0f10b78e823c1beca05ed802c0915b77ab7b9","observation_id":"b4c7bded-fa3d-4afd-9163-31918015726a","resolution":{"observed_at":"2026-08-08T16:36:51.198567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.178184Z","title":"Log-concavity and strong log-concavity: a review","venue":null,"work_id":"8d126570-8041-4a11-87dc-6f42fa06365b","year":2014},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.837241Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:94e702fabb9e70901d567bd540bc1b80e7cbf8a590b09916bdfb70d970b1ca78","observation_id":"67b8f2f7-bc02-4118-86a8-161d5fc1a3b7","resolution":{"observed_at":"2026-08-08T16:36:51.183235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:50.842095Z","title":"Approximation theorems of mathematical statistics","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.842095Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:c154fd2b87cadfe32ac8e193a09d71cf0955956f0ac6a3c6a38380ee42d786e2","observation_id":"d99d71ee-da7f-4d94-9a4c-f8c455d1f8d3","resolution":{"observed_at":"2026-08-08T16:36:50.842095Z","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":"2026-08-08T16:36:51.153635Z","title":"Shephard and M","venue":null,"work_id":"29703244-af7e-4366-8c03-db41c4ae6c8d","year":1997},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.846869Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:b6a097561b42a53e25b54a425856fa961c02afaa7471a0bd6a326b8f008bea8f","observation_id":"201cc44c-0827-4b0a-8672-569cdbbc609b","resolution":{"observed_at":"2026-08-08T16:36:51.158005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.139514Z","title":"Maximum mean discrepancy","venue":null,"work_id":"b846d4a2-ac87-4c6b-bec7-5b88483b3ac9","year":2006},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.852025Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:402b2e0900f04b01e9e51239423c7e2aa5c325562c5fb4ef8b46818c068d1d76","observation_id":"72637cc5-0528-4004-b3b8-a0e5c7e5c2cc","resolution":{"observed_at":"2026-08-08T16:36:51.144096Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.124644Z","title":"Obstacles to high-dimensional particle filtering","venue":null,"work_id":"1eedc4ad-6640-4313-b4bf-9ac749cd9a8f","year":2008},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.856880Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:ecc9effba47dfd23986965486ea7315681bb76ca1896d5fe326ebd04d851cf3f","observation_id":"2b77c6b8-1d20-40f3-bf01-8d995cb3da50","resolution":{"observed_at":"2026-08-08T16:36:51.129764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.108774Z","title":"High-dimensional ensemble kalman filter with localization, inflation, and iterative updates","venue":null,"work_id":"2ce7dc5c-e53f-4713-9196-7f527642bf48","year":2024},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.861592Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:d327273c1797f7d27c910b459d11ceec0601a208c5a1abdd64638874f07383df","observation_id":"c999576f-eb05-47e7-8e24-6f1d23a09e1e","resolution":{"observed_at":"2026-08-08T16:36:51.114186Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.092174Z","title":"Adaptivity of deep relu network for learning in besov and mixed smooth besov spaces: optimal rate and curse of dimensionality","venue":null,"work_id":"071960fc-553c-46f8-8cd4-025a4fd58acb","year":2019},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.866273Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:4a5c20b2f92b78b1cd2074514d881cd03335f71e7d4b0eb25f6976ac9cf71317","observation_id":"15e5f6e0-56be-43e8-860e-51d66bff6288","resolution":{"observed_at":"2026-08-08T16:36:51.097185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:50.871233Z","title":"High-Dimensional Statistics: A Non-Asymptotic Viewpoint","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.871233Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:10af05232de5433ccf4c47481ba3cb2801671ff07e9832db117a5454eb1c36e3","observation_id":"93fede82-ad61-4204-9c2d-2f98a4164bbf","resolution":{"observed_at":"2026-08-08T16:36:50.871233Z","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":"2026-08-08T16:36:51.076367Z","title":"The implicit and explicit regularization effects of dropout","venue":null,"work_id":"14e3b762-bd96-429f-9df1-0d043a004161","year":2020},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.876167Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:b0a8b2b74e75c9882521d9c8a5e2a6b6a2a50fb89be820c69bf3113c8c5124ac","observation_id":"cf4fe03d-b066-42fe-a29b-c6e67160b7f3","resolution":{"observed_at":"2026-08-08T16:36:51.081248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.060976Z","title":"Bayesian learning via stochastic gradient langevin dynamics","venue":null,"work_id":"501d2c84-cabc-4fc0-82e7-86c1ddf74698","year":2011},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.880862Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:2809f966044673ba27e652ded21dd0c16ad303ef05172f2a9ece2d959292c217","observation_id":"80bc8440-eac8-4469-8dbe-b2cafaadaaa7","resolution":{"observed_at":"2026-08-08T16:36:51.065991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.045248Z","title":"A note on the particle filter with posterior gaussian resampling","venue":null,"work_id":"591369ac-b703-4d8f-aa42-59cb33a78045","year":2006},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.885629Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:a425978bbe21749001da0ed7029b1001168c917cf28b51c197b1c4378c599a9d","observation_id":"0ffa4ff8-1a0e-4979-b84d-2686c6b4e598","resolution":{"observed_at":"2026-08-08T16:36:51.050561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T16:36:51.029262Z","title":"Normalizing flow neural networks by jko scheme","venue":null,"work_id":"e5c7b45a-9b19-4d14-a49b-a02b5b8a2f03","year":2024},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.890622Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:1755bb91f8784d3bab55315ebe1dfef047e6b2433024b1ba086f7f26deb7f23b","observation_id":"6002fc41-b440-4c07-91a0-75e65f43cca4","resolution":{"observed_at":"2026-08-08T16:36:51.034366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.04622","last_updated":"2020-12-29T17:24:48Z","snapshot_observed_at":"2026-08-10T19:23:16.164902Z","submitted_at":"2020-11-09T18:32:22Z","title":"On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.04622","snapshot_observed_at":"2026-08-08T16:36:50.895385Z","title":"On function approximation in reinforcement learning: Optimism in the face of large state spaces","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.895385Z"},"links":{"cited_paper":"/paper/2011.04622","citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:cd8783b3c82158210158358e857df421d5e03cadc950822db4d97eff25e18a5f","observation_id":"74abe2e2-e515-4805-994b-41348eddbce1","resolution":{"observed_at":"2026-08-08T16:36:50.895385Z","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":"2026-08-08T16:36:50.900513Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-08T16:36:50.900513Z"},"links":{"citing_paper":"/paper/2502.06165"},"observation_digest":"sha256:15e34a6b977ea04ae36911b003ed371af6607c98cfcbf57e605b86479b183d96","observation_id":"6201f0b9-e3e8-43c8-8f73-b1701b7ed45f","resolution":{"observed_at":"2026-08-08T16:36:50.900513Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.06165","last_updated":"2025-02-10T05:31:35Z","latest_version":1,"primary_category":"stat.ME","snapshot_observed_at":"2026-08-09T01:17:04.826489Z","submitted_at":"2025-02-10T05:31:35Z","title":"Adversarial Transform Particle Filters"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":13,"verified_exact":1,"verified_fuzzy":48},"total_outbound_references":62},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2502.06165."}