{"as_of":"2026-08-17T14:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2e7355f6ad1ffc61b4f39fb2df4b2aac14495c575e8ada5b3a9e70a55703a06c","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T20:07:07.434649Z","state":"measured"},{"denominator":25,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":25,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:07:50.564959Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T05:07:51.536238Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"cited_work":{"arxiv_id":"2502.05155","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.05155","snapshot_observed_at":"2026-08-07T05:07:51.536238Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","venue":"cs.LG","work_id":"592120c9-bf63-49e8-8ac0-905c5e2828a6","year":2025},"citing_paper":{"arxiv_id":"2506.08884","last_updated":"2025-06-10T15:13:48Z","snapshot_observed_at":"2026-08-15T11:57:35.941379Z","submitted_at":"2025-06-10T15:13:48Z","title":"InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:07:50.564959Z"},"links":{"cited_paper":"/paper/2502.05155","citing_paper":"/paper/2506.08884"},"observation_digest":"sha256:5132ce8e48d469c924c18697aec7188b4e18691b7ad99bd176e0ecb9147c5a9c","observation_id":"976cb110-fc71-46e9-a03f-91d0c7c33117","resolution":{"observed_at":"2026-08-07T05:07:51.609597Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.05155/citation-record","integrity":"/paper/2502.05155/integrity","json":"/paper/2502.05155/citation-record.json","paper":"/paper/2502.05155"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:07:07.716841Z","title":"A probabilistic interpretation of canonical correlation analysis,","venue":null,"work_id":"08ee64b9-53e5-49a2-9377-94b5fc15b326","year":2005},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.345259Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:7aceacd6642e2afbb5f95caebab8a92974e6ac5a64d6a474b8ec31c8470802a6","observation_id":"4d8ff32c-4f77-4d49-ae9b-ddea39835333","resolution":{"observed_at":"2026-08-08T20:07:07.720720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.705257Z","title":"Probabilistic approach to detecting dependencies between data sets,","venue":null,"work_id":"5b230717-b2a6-41b5-8e8b-2b1c9a5cacc4","year":2008},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.349928Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:53fdea4c1379cd3b1086ffc8a69ff3818d00dd0666e446c7f3618936d80ab151","observation_id":"7f76b05b-174e-4d72-8d8f-0ba028669526","resolution":{"observed_at":"2026-08-08T20:07:07.709112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.694445Z","title":"Probabilistic partial least squares model: Identifiability, estimation and application,","venue":null,"work_id":"fe19a87c-9967-4af3-bfc1-def12687960a","year":2018},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.353655Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:b64cbb8251da94ee03c38ebda4afed3bdc24d218825626cc824f857a5810dffd","observation_id":"9c424dc9-7f06-4174-bef0-7cbca0278ac2","resolution":{"observed_at":"2026-08-08T20:07:07.698196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.357358Z","title":null,"venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.357358Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:b93c3baddff744cda6e2c0531fe2ae4fe85221e1ee60654070e66cacf5a25bb5","observation_id":"13a07550-031f-44fe-9d46-4ce85dec96e3","resolution":{"observed_at":"2026-08-08T20:07:07.357358Z","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":"2026-08-08T20:07:07.675790Z","title":"Bayesian sparse partial least squares,","venue":null,"work_id":"f5c0e8f4-68ca-4382-9c2b-ba57ae9f51e4","year":2013},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.361162Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:a5f1c28f6ca82fcf649e83f7a6d35792a2de3617e4cc8c6e118001c412a8eadb","observation_id":"27b92396-32c4-410d-8cc9-19b93989edd1","resolution":{"observed_at":"2026-08-08T20:07:07.679468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.665095Z","title":"Dynamic latent variable analytics for process operations and control,","venue":null,"work_id":"454b43e3-537f-42a5-b853-56d180ff5a39","year":2018},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.364951Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:2380b0b637a582aa98c702c483a1d46a94f99b5e9e60a4d256b89d1dcc50f437","observation_id":"1daf22f8-756f-4fcb-82ea-ec297fbd91ba","resolution":{"observed_at":"2026-08-08T20:07:07.668912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.652993Z","title":"Dynamic prob- abilistic cca for analysis of affective behavior and fusion of continuous annotations,","venue":null,"work_id":"491d8633-7b80-49fa-8d15-b0f388f6ad47","year":2014},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.368725Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:13479ee9abe26a5bc3a1964a54b9828ec950ce5cee67ae8d0ff84dac5512e26f","observation_id":"170d3939-0ff7-4bc2-986b-c26c17a78aa1","resolution":{"observed_at":"2026-08-08T20:07:07.657088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.641159Z","title":"Structured inference networks for nonlinear state space models,","venue":null,"work_id":"b1d03a11-c36c-4fdc-818c-4d1ae4f81bbb","year":2017},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.372261Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:94122b549d5881f54e43d459344794f4f57caf0e3f49eaae2cbc312c18dcd16a","observation_id":"08b79d04-4758-4904-8609-2b85db6865cd","resolution":{"observed_at":"2026-08-08T20:07:07.645273Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.629347Z","title":"A view of the em algorithm that justifies incremental, sparse, and other variants,","venue":null,"work_id":"3bd9596f-ead2-4f2e-b2ca-dfa7a341202d","year":1998},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.375695Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:7f56cb96d86fc99d5b959d32280cbb5eca2cb4c3f6a038512f14afb491f03415","observation_id":"78ce3a8f-f64c-4b5b-be72-27836d68d5fa","resolution":{"observed_at":"2026-08-08T20:07:07.633620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6114","last_updated":"2022-12-10T21:04:00Z","snapshot_observed_at":"2026-08-14T23:50:45.029465Z","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":"2026-08-08T20:07:07.379581Z","title":"Auto-encoding variational bayes,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.379581Z"},"links":{"cited_paper":"/paper/1312.6114","citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:b2af11ffb86e9d542b7d6352e761261702d21c14844e4c51192c21ba96ac1e8c","observation_id":"e7cd1d04-a960-4274-bda6-88040b44cf39","resolution":{"observed_at":"2026-08-08T20:07:07.379581Z","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":"2026-08-08T20:07:07.383883Z","title":"Variational inference: A review for statisticians,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.383883Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:06e8b8595b0545baaa07c56c9a01b8ebcac7e6ccfd49a3e0471d0ddd5e68e4d4","observation_id":"ef2c2b78-dcaf-4041-a042-04a13557641c","resolution":{"observed_at":"2026-08-08T20:07:07.383883Z","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":"2026-08-08T20:07:07.612369Z","title":"A unifying review of linear gaussian models,","venue":null,"work_id":"84963ca0-92b0-4a20-a24a-5b8cc840524c","year":1999},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.387913Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:b4da2e5efa72c07b7e3ac4a50e00ef4696a49440f07615e9d5b45b5962114c16","observation_id":"74f9c782-07c5-4aef-ab7c-f9bccb6d8250","resolution":{"observed_at":"2026-08-08T20:07:07.615985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.600950Z","title":"Auto-encoding variational bayes,","venue":null,"work_id":"8cb604d6-2491-494d-bce5-bd5231a9a9de","year":2014},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.393521Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:c13c84433472b2a7ebff67ea62f97f4a4686ed0631a12ad466066c93017c7f28","observation_id":"594f69b9-a20c-42c6-b56d-6a30547b118e","resolution":{"observed_at":"2026-08-08T20:07:07.604768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.10145","last_updated":"2019-06-10T21:43:02Z","snapshot_observed_at":"2026-08-14T16:57:26.695252Z","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":"2026-08-08T20:07:07.397111Z","title":"Cyclical annealing schedule: A simple approach to mitigating kl vanishing,","venue":null,"work_id":null,"year":1903},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.397111Z"},"links":{"cited_paper":"/paper/1903.10145","citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:fe705da363e8651a810228105664d4c2cc5846e410c37f564405b39b97aa0baa","observation_id":"092812b7-b896-4964-8215-170fbd50f2dd","resolution":{"observed_at":"2026-08-08T20:07:07.397111Z","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":"2026-08-08T20:07:07.401068Z","title":"Variational inference with normalizing flows,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.401068Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:255bb03458f384451a96a765e124db7627ee9a66d4ac62d017780731f765ce78","observation_id":"957fccd1-25a9-4984-8152-be474782f049","resolution":{"observed_at":"2026-08-08T20:07:07.401068Z","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":"2026-08-08T20:07:07.582014Z","title":"Improved variational inference with inverse autoregressive flow,","venue":null,"work_id":"9fefed95-4971-4d4c-b36e-a2e9b33285d6","year":2016},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.404818Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:c857f03f42f1d18c019d550d091907ca1b372dcacc510415a8cf67fd9b6ab90e","observation_id":"5b7cf2b6-777a-4681-a783-0cb921bffec7","resolution":{"observed_at":"2026-08-08T20:07:07.585835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.570985Z","title":"Normalizing kalman filters for multivariate time series analysis,","venue":null,"work_id":"b3f5e015-8f6e-42d6-8e58-db5b31a4837f","year":2020},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.408599Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:90dffae77f8543be6c84a5593e737957f8d5b1bc84502c5d21f71a1c672e96a1","observation_id":"6c08d8e8-15c3-4712-9fcc-908f4423b411","resolution":{"observed_at":"2026-08-08T20:07:07.574743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.559903Z","title":"Improving sequential latent variable models with autoregressive flows,","venue":null,"work_id":"3d4cbb76-20c2-4e7c-b045-801721b08c6b","year":2020},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.412017Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:a81141e3c87cfae34deb04dafbaf230ffb27ad5d4da8cce66575a3b53e894d8a","observation_id":"5a63f4bf-bbef-416a-8199-44d2014a905d","resolution":{"observed_at":"2026-08-08T20:07:07.563620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.547774Z","title":"Factorial hidden markov mod- els,","venue":null,"work_id":"6856db26-0161-419b-88ea-a263a05dec66","year":1995},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.415490Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:2a01eeea2450cde337a1412be12d5bf15c55ddcf1ac18cffcbe1064a750ef157","observation_id":"59205c57-f1fa-4e3a-8c18-9572913f9eaa","resolution":{"observed_at":"2026-08-08T20:07:07.552343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-14T18:51:16.666127Z","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":"2026-08-08T20:07:07.419164Z","title":"Adam: A method for stochastic optimization,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.419164Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:3aa1555468fa3c1e32afd4c2d02bea6cce22428c0c504b1cb89509663197058b","observation_id":"5aa9ce4f-bd5d-4994-a84f-7ef622ec9622","resolution":{"observed_at":"2026-08-08T20:07:07.419164Z","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":"2026-08-08T20:07:07.533050Z","title":"Pyro: Deep universal probabilistic programming,","venue":null,"work_id":"7cfa3746-62d1-407e-b947-2050c5261a62","year":2019},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.423894Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:668d0c6650e65da5971d38935ddb69783b45e5721d417d155f21fa54391de3af","observation_id":"e795c171-db67-4fb9-b75d-6a9b59f59941","resolution":{"observed_at":"2026-08-08T20:07:07.537850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.517245Z","title":"S&P 500 Stock Data Dataset,","venue":null,"work_id":"4fa37d87-d590-474e-91da-6125378b9e97","year":2024},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.427905Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:ffe96005b286905bc32d20ac93a1b334b10f3d2f5c3788add3cbf37a38877308","observation_id":"c85d7a09-7e81-47d5-8a11-7e466b4c0752","resolution":{"observed_at":"2026-08-08T20:07:07.521956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-08T20:07:07.501401Z","title":"A recurrent latent variable model for sequen- tial data,","venue":null,"work_id":"a4d1d221-bdeb-45e7-b23e-ce88360aec61","year":2015},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.431340Z"},"links":{"citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:016c8b35b61aba0b45cfbe04d9356ba4164d3712719bcdc1538ddb555b861bd9","observation_id":"ec307597-dc9e-4ed0-b467-b1e930e1e0c9","resolution":{"observed_at":"2026-08-08T20:07:07.507354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.12595","last_updated":"2022-07-04T16:11:08Z","snapshot_observed_at":"2026-08-15T10:22:21.267511Z","submitted_at":"2020-08-28T11:49:33Z","title":"Dynamical Variational Autoencoders: A Comprehensive Review","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.12595","snapshot_observed_at":"2026-08-08T20:07:07.434649Z","title":"Dynamical variational autoencoders: A comprehensive review,","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-08T20:07:07.434649Z"},"links":{"cited_paper":"/paper/2008.12595","citing_paper":"/paper/2502.05155"},"observation_digest":"sha256:89dfac4cee39aa9cebdc18741dab7f2cf206262e2ccea36b0134354bbe13ce18","observation_id":"b95c1d6f-25ee-457f-a0c6-b69b9922fd04","resolution":{"observed_at":"2026-08-08T20:07:07.434649Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.05155","last_updated":"2025-02-07T18:37:57Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T10:22:58.921729Z","submitted_at":"2025-02-07T18:37:57Z","title":"Deep Dynamic Probabilistic Canonical Correlation Analysis"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":17},"total_outbound_references":24},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2502.05155."}