{"as_of":"2026-08-07T12:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ffa0cd3ce6befbd8adfe8c68477eb08b5a4d2d79c4c194558881de450e16083f","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-18T14:19:22.481700Z","state":"measured"},{"denominator":56,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":56,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-19T20:59:55.644530Z","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":"2026-05-19T21:02:47.343534Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"cited_work":{"arxiv_id":"2509.20098","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.20098","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","venue":"cs.LG","work_id":"b3ebb182-44ac-4e34-bae6-fd15828989b0","year":2025},"citing_paper":{"arxiv_id":"2605.16818","last_updated":"2026-05-16T05:23:49Z","snapshot_observed_at":"2026-07-06T23:27:52.850836Z","submitted_at":"2026-05-16T05:23:49Z","title":"Observation-Aligned Mask Priors for Learning Physical Dynamics from Authentic Occlusions","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-19T20:59:55.644530Z"},"links":{"cited_paper":"/paper/2509.20098","citing_paper":"/paper/2605.16818"},"observation_digest":"sha256:6e854fa85fc65d201d2bbd5655609b6f7952a10c71ca99f0db8d63d416aa4e16","observation_id":"a6800139-8486-4a5b-bf2c-447eb54ca2db","resolution":{"observed_at":"2026-05-19T21:02:47.345057Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2509.20098/citation-record","integrity":"/paper/2509.20098/integrity","json":"/paper/2509.20098/citation-record.json","paper":"/paper/2509.20098"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.03725","last_updated":"2024-09-23T16:38:43Z","snapshot_observed_at":"2026-08-06T06:35:01.735374Z","submitted_at":"2023-10-05T17:46:31Z","title":"Stochastic interpolants with data-dependent couplings","version":3},"cited_work":{"arxiv_id":"2310.03725","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.03725","snapshot_observed_at":"2026-07-04T11:59:51.576995Z","title":"Stochastic interpolants with data-dependent couplings","venue":null,"work_id":"9d29254d-1e1b-42c3-ac06-35e6ef5d5d16","year":2023},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2310.03725","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:380e276a955f5c9ec9d5cab633a69046f2dca97f4884eef2f86e9274ff0ceea8","observation_id":"e9a66181-3da2-4f2a-9efb-e14baa9ef6c9","resolution":{"observed_at":"2026-05-18T14:21:28.285109Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Infinite dimensional compressed sensing from anisotropic measurements and applications to inverse problems in pde","venue":null,"work_id":"6a6acd65-8efc-4f09-989e-9527c566431b","year":2021},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:5a7651f834ef3f371d3b52381ec93cecf2905b13c40dd873c5deaaa0335c97dc","observation_id":"714a076e-8f48-44a3-ab71-a22f4f41854a","resolution":{"observed_at":"2026-05-18T14:21:29.036514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Navier-stokes, fluid dynamics, and image and video inpainting","venue":null,"work_id":"0e5e01d6-f362-4369-a462-e6d3f613fb06","year":2001},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:d153ff06795974f93b20391a5603347a3089e1aded9829f02d94e96006fc8ca6","observation_id":"1d3fc751-4e26-4991-b703-bb947fca0b06","resolution":{"observed_at":"2026-05-18T14:21:29.056217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pattern recognition and machine learning, volume 4","venue":null,"work_id":"3b5124d0-8225-4b43-b7a1-26b9220875a8","year":2006},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:a41469d5336182ec33d6bdcdca4e6ced20dcd53c3df283399e9663c7dd24e919","observation_id":"190d67ea-5dab-4e8b-bb5e-c9bb7869560c","resolution":{"observed_at":"2026-05-18T14:21:29.025262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Promising directions of machine learning for partial differential equations","venue":null,"work_id":"420af4a6-2e7d-4de3-9be9-ec8866560461","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:7dd34fb615c4c60291e0a5e29caf2cdb3477dba0695bc208415681e47694b7e0","observation_id":"8f370c6b-41df-4d57-bf59-ec9a26bc3180","resolution":{"observed_at":"2026-05-18T14:21:29.013635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Navier-stokes dataset of isotropic turbulence in a periodic box","venue":null,"work_id":"e886520b-c289-47bd-b647-e7d6f8225f1b","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:23b709b7c68136efef6e86cf15c4b76a5ecdd68c985697afa29889dae51791f1","observation_id":"9e728229-1703-44fb-872f-a98506dfdf92","resolution":{"observed_at":"2026-05-18T14:21:29.124494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Difflight: a partial rewards conditioned diffusion model for traffic signal control with missing data","venue":null,"work_id":"343c0b8f-9efa-49ff-a46d-dc9317ddd421","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:3f13bc15049b6445acdf4dc1b08a4d56ca9563864977c3143f2a69f517e7e37c","observation_id":"6f5ff86a-7937-42af-8b9a-6cbbb8850415","resolution":{"observed_at":"2026-05-18T14:21:29.113296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Rethinking the diffusion models for missing data imputation: A gradient flow perspective","venue":null,"work_id":"0a94c5d0-2843-4a81-b039-1665e22480de","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:9c25d6394c1a5eafea431e7a5743a677b214542bf70fd40465bc076966530ce0","observation_id":"10efa039-7b68-4c5b-a160-2537e95428ac","resolution":{"observed_at":"2026-05-18T14:21:29.104489Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14687","last_updated":"2024-05-20T04:23:45Z","snapshot_observed_at":"2026-08-03T03:59:22.374270Z","submitted_at":"2022-09-29T11:12:27Z","title":"Diffusion Posterior Sampling for General Noisy Inverse Problems","version":4},"cited_work":{"arxiv_id":"2209.14687","doi":"10.1101/2025.01.08","metadata_source":"pith","pith_arxiv_id":"2209.14687","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Diffusion Posterior Sampling for General Noisy Inverse Problems","venue":"stat.ML","work_id":"083ab9fb-05f0-41e1-9628-982017eac344","year":2022},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2209.14687","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:a69904cdac169f1a3f9b59d1aac04f36e5853c8765d029f64befc555c8f91792","observation_id":"04c817ef-449b-410b-a147-28eb19256812","resolution":{"observed_at":"2026-05-18T14:21:28.305138Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Artificial intelligence for weather forecasting","venue":null,"work_id":"f7cd8167-ad4c-4627-9d3e-e8740cf0355b","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:2e6be029a99138a6ba8d723f91801ed906786668b14fdf6f0b89028768d5dfc0","observation_id":"62a5ba14-bfee-402d-a7d6-c10d327b3552","resolution":{"observed_at":"2026-05-18T14:21:29.069662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Latentpaint: Image inpainting in latent space with diffusion models","venue":null,"work_id":"25d32b6c-1909-46f3-b5e9-4d01aa17d466","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:7c9ba4af59703cd6fc7579585afebab917d3e6531160854bd7a8e803c7d143ad","observation_id":"acdecfaa-9429-48a1-ac31-203c15d0975b","resolution":{"observed_at":"2026-05-18T14:21:29.073070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sadi: Similarity-aware diffusion model-based imputation for incomplete temporal ehr data","venue":null,"work_id":"89fb3496-3b0b-45ab-b76c-eb2df778a915","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:c0efcf2f6d17972585ad91f2bd7bd4e869fb1b654b1518faf481bf68c6022265","observation_id":"937e4da3-a278-41f3-80c8-2910f2b66caf","resolution":{"observed_at":"2026-05-18T14:21:29.062546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ambient diffusion: Learning clean distributions from corrupted data","venue":null,"work_id":"92891a28-0e5a-4640-b4d5-b84f178fb0fc","year":2023},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:ea7a4272d7143571596a01e834b32d5433acd78231354017a2dd5ca9ffb3215e","observation_id":"a42c0e8e-9ab6-4e4b-91a0-513153dee3a4","resolution":{"observed_at":"2026-05-18T14:21:29.118902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning signal-agnostic manifolds of neural fields","venue":null,"work_id":"e3b3277b-3e3f-474a-8d64-b9c6a3de3b03","year":2021},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:91430b7d460239a9a74ec0aac8280d81da25f05dd9f02f14702fde5c57c21fef","observation_id":"5fce4b5f-f05f-4557-bbb2-f70c1d07d4ed","resolution":{"observed_at":"2026-05-18T14:21:29.048237Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Causal deciphering and inpainting in spatio-temporal dynamics via diffusion model","venue":null,"work_id":"db2c3cd1-4356-4ed0-b64a-9e7ff2339014","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:27f05c562b16120faa125896617ef3d7b32707ae7518ccd144b50423487f871d","observation_id":"4035f401-5d6a-4df2-b3df-75c82cdabdf4","resolution":{"observed_at":"2026-05-18T14:21:29.033484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.12204","last_updated":"2022-11-10T13:32:44Z","snapshot_observed_at":"2026-08-07T11:17:13.826645Z","submitted_at":"2022-01-28T15:59:58Z","title":"From data to functa: Your data point is a function and you can treat it like one","version":3},"cited_work":{"arxiv_id":"2201.12204","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.12204","snapshot_observed_at":"2026-07-03T17:08:42.732388Z","title":"From data to functa: Your data point is a function and you can treat it like one.arXiv preprint arXiv:2201.12204","venue":null,"work_id":"0284c2c8-1587-4b02-92a6-024906aba9d2","year":2022},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2201.12204","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:80097010a4aa8d953d36d8f082d36ad4671ec6725a3917e257a94dcc5cfd9ffa","observation_id":"9610a099-0523-46d4-bde2-94e51a89b59b","resolution":{"observed_at":"2026-05-18T14:21:28.289260Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tweedie’s formula and selection bias","venue":null,"work_id":"23a3438b-ffdc-4092-b807-f6f222d3749b","year":2011},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:780b74fbaeea5f79ec0949683a27b0d8c896c22816a99c843aeef40b480bbc16","observation_id":"255db185-c13a-499b-8ccc-322397cdbef1","resolution":{"observed_at":"2026-05-18T14:21:29.042519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.00557","last_updated":"2025-05-31T13:26:51Z","snapshot_observed_at":"2026-08-07T12:00:35.050198Z","submitted_at":"2025-05-31T13:26:51Z","title":"Score Matching With Missing Data","version":1},"cited_work":{"arxiv_id":"2506.00557","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.00557","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Juraj Gottweis, Wei-Hung Weng, Alexander Daryin, Tao Tu, Anil Palepu, Petar Sirkovic, Artiom Myaskovsky, Felix Weissenberger, Keran Rong, Ryutaro Tanno, et al","venue":null,"work_id":"ba776978-122d-42d7-b7c5-e18b1288beab","year":2025},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2506.00557","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:d148acbb8c9947099376789d3f8f30f4579b2ac620cc953e212e2a593f3ce4e8","observation_id":"1cd868e0-86dd-48ca-b904-c908ea96ec2a","resolution":{"observed_at":"2026-05-18T14:21:28.328718Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Machine learning and deep learning in synthetic biology: Key architectures, applications, and challenges","venue":null,"work_id":"a26c011b-de2b-4428-a311-8d96b960f8c5","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:c3bcc5c6dffc950f9af4e8dec24a58b51657f2ccf19da54ca3d5d115aaae910f","observation_id":"09f80d09-8160-41b7-8718-9fd4731f35fc","resolution":{"observed_at":"2026-05-18T14:21:29.045198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The era5 global reanalysis","venue":null,"work_id":"db32e64d-84f0-4150-9c4f-9b47af97aaa4","year":1999},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:5bcef2923e506af726dbc9b5b7e9efe688b4c94ca04eb4049ac93321f00ab8ba","observation_id":"6bed7d13-4276-46c6-a9b1-def8b088841e","resolution":{"observed_at":"2026-05-18T14:21:29.053493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Denoising diffusion probabilistic models","venue":null,"work_id":"fafa2ee6-9642-4e76-9770-d1aae476a8d3","year":2020},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:f7b6863bed40116df82c715d3d5afcd28fa2e28e1f08dcd672d2c93a818e0797","observation_id":"81358fea-02d4-4e34-9c53-1e5a46d9c671","resolution":{"observed_at":"2026-05-18T14:21:29.039477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Temporally coherent completion of dynamic video","venue":null,"work_id":"8e9f2bf1-f63f-4b01-ab72-33211607df53","year":2016},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:450c3c4396c113931c8a4b82867861ec8193a1ed982802d5f4f50331955f4aa0","observation_id":"a5c9f384-0d60-49d6-8b13-4e54c0414b79","resolution":{"observed_at":"2026-05-18T14:21:29.059494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17763","last_updated":"2024-11-01T00:08:54Z","snapshot_observed_at":"2026-07-06T18:36:51.761148Z","submitted_at":"2024-06-25T17:48:24Z","title":"DiffusionPDE: Generative PDE-Solving Under Partial Observation","version":2},"cited_work":{"arxiv_id":"2406.17763","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.17763","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Diffusionpde: Generative pde-solving under partial observation","venue":null,"work_id":"79e05ffd-b20b-4047-948b-5a46557c85dc","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2406.17763","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:c2c20619e6b2c64d07b5624436a9d401e25fc81edc412161ee76cc6156c3dd38","observation_id":"1c5d2ed1-de46-472f-a980-a8ce0d5edcd3","resolution":{"observed_at":"2026-05-18T14:21:28.276864Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.12871","last_updated":"2021-03-18T13:32:09Z","snapshot_observed_at":"2026-07-06T09:31:50.012114Z","submitted_at":"2020-06-23T10:06:21Z","title":"not-MIWAE: Deep Generative Modelling with Missing not at Random Data","version":2},"cited_work":{"arxiv_id":"2006.12871","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2006.12871","snapshot_observed_at":"2026-06-29T23:14:01.949750Z","title":"not-miwae: Deep generative modelling with missing not at random data","venue":null,"work_id":"8a312744-c7d2-457c-ad43-8f00560b48d6","year":2006},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2006.12871","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:9dbf0cae848e6c91356a5c3e1e4d2494f32997044bca3cee4594a2112dc67475","observation_id":"f26e0f8b-807d-410c-b097-a40e80c2d85e","resolution":{"observed_at":"2026-05-18T14:21:28.301265Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Analyzing and improving the training dynamics of diffusion models","venue":null,"work_id":"69629c8a-67a2-4277-9332-c21711cc62a5","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:a6399f997e191b3fa7c9d7f861d450e3c233c0372ff5a374ce6be0e9396b62c8","observation_id":"bf63928d-bd67-4c38-a8d2-bb0493561b16","resolution":{"observed_at":"2026-05-18T14:21:29.030688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Noise2score: tweedie’s approach to self-supervised image denoising without clean images","venue":null,"work_id":"a1452e04-184d-4b66-8e78-bb47960b6ad5","year":2021},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:2d2cdf25d35d2240f62b0ab5cc966c2aa1afc714592f0514408ef6a0083f19fc","observation_id":"c3d1b892-fcb4-45ca-9dd3-cabc143d6848","resolution":{"observed_at":"2026-05-18T14:21:29.088505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Diffusion models for audio restoration: A review [special issue on model-based and data-driven audio signal processing]","venue":null,"work_id":"72609190-5ab4-4978-b339-db4b33d6c84c","year":2025},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:e626843c2be6225417520c000d19a756f66df8143c0062bc826f927e3ebd466f","observation_id":"5ee34003-575a-4d54-b833-18d52792668a","resolution":{"observed_at":"2026-05-18T14:21:29.022164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning from irregularly-sampled time series: A missing data perspective","venue":null,"work_id":"707e4061-6fc3-43e5-937d-c1c36060acd7","year":2020},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:c76e1a18571efb5e7877463450f25176bec222cbcc00bbb815626e7ba76568d0","observation_id":"2a20419d-2578-45e2-b047-45b04000110f","resolution":{"observed_at":"2026-05-18T14:21:29.016436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.09599","last_updated":"2019-02-25T20:24:35Z","snapshot_observed_at":"2026-07-06T07:35:21.645806Z","submitted_at":"2019-02-25T20:24:35Z","title":"MisGAN: Learning from Incomplete Data with Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":"1902.09599","doi":null,"metadata_source":"pith","pith_arxiv_id":"1902.09599","snapshot_observed_at":"2026-07-09T22:56:37.660752Z","title":"MisGAN: Learning from Incomplete Data with Generative Adversarial Networks","venue":"cs.LG","work_id":"db7a8fb6-ff9c-45b1-ab29-d0b17498abc5","year":2019},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/1902.09599","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:d8191f724ffa5a39cea8465996e20d49a29a715eec3881bffd34a67eddfed80e","observation_id":"b32b3baa-33f4-4b71-b1fa-191097a4970e","resolution":{"observed_at":"2026-05-18T14:21:28.268713Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.08895","last_updated":"2021-05-17T03:12:33Z","snapshot_observed_at":"2026-07-06T10:05:26.653366Z","submitted_at":"2020-10-18T00:34:21Z","title":"Fourier Neural Operator for Parametric Partial Differential Equations","version":3},"cited_work":{"arxiv_id":"2010.08895","doi":"10.1016/0375-9601(81)90165-1","metadata_source":"pith","pith_arxiv_id":"2010.08895","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Fourier Neural Operator for Parametric Partial Differential Equations","venue":"cs.LG","work_id":"cc647655-121e-4055-85f0-fad4530ea964","year":2020},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2010.08895","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:a1ed656584d8d3a15a0a9f0506bae96aad13c20e0a8f45525c00573becc52fad","observation_id":"6204665a-747b-4151-99ee-d4cbbf872ac8","resolution":{"observed_at":"2026-05-18T14:21:28.272553Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.05872","last_updated":"2023-05-26T02:55:08Z","snapshot_observed_at":"2026-07-06T14:50:53.033420Z","submitted_at":"2023-02-12T08:35:39Z","title":"I$^2$SB: Image-to-Image Schr\\\"odinger Bridge","version":3},"cited_work":{"arxiv_id":"2302.05872","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.05872","snapshot_observed_at":"2026-07-04T03:39:29.838025Z","title":"i2- sb: Image-to-image schr \\” odinger bridge","venue":null,"work_id":"7f83675d-fa27-444f-9fb1-686a9c4ae3c3","year":2023},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2302.05872","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:134a17781974f00b5f13fcf5f8abf01e3a530d87552d255012faba46d91f037d","observation_id":"1cab3cde-813b-4f21-b1dc-22b74baae53a","resolution":{"observed_at":"2026-05-18T14:21:28.314137Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Repaint: Inpainting using denoising diffusion probabilistic models","venue":null,"work_id":"8cb44891-5a76-4092-a489-99b79b5db752","year":2022},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:b4a74ae9ad6d08f6d2be2564a813e308bb905b92dfe977f3abc62ab6a61a32e1","observation_id":"d8c4e09f-5d03-49cd-9341-22c7f7766060","resolution":{"observed_at":"2026-05-18T14:21:29.019396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Physics-informed neural networks for pde problems: a comprehensive review","venue":null,"work_id":"9c0facc7-86bd-4d8a-a2d0-2e4e91fec62b","year":2025},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:443f75d09cc7c651b224d4fbb461f05a2fb4fc15ed1360c04ee5ea97a8e7068e","observation_id":"18305966-92c1-485f-9852-04072f479fc9","resolution":{"observed_at":"2026-05-18T14:21:29.028017Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vaem: a deep generative model for heterogeneous mixed type data","venue":null,"work_id":"1e540401-35f9-4343-b371-a06b6322cf40","year":2020},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:d0981695c7793156865696e4674856631de68e15ac4dbc9e469391c9c01c541c","observation_id":"77606f06-a4b8-4eb6-a832-3fffca300074","resolution":{"observed_at":"2026-05-18T14:21:29.050885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"When physics meets machine learning: A survey of physics-informed machine learning","venue":null,"work_id":"738bef1e-e648-4d82-8fd6-d8d2594524ba","year":2025},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:2ff771dc67b0802f2f38b94b29ef1a46401b8bb785693167c8ca6d828d7433a2","observation_id":"30d954b9-43ea-41f9-aeb3-4d1e848dbc53","resolution":{"observed_at":"2026-05-18T14:21:29.121529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.00467","last_updated":"2023-07-02T03:49:47Z","snapshot_observed_at":"2026-07-06T15:49:19.631265Z","submitted_at":"2023-07-02T03:49:47Z","title":"MissDiff: Training Diffusion Models on Tabular Data with Missing Values","version":1},"cited_work":{"arxiv_id":"2307.00467","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.00467","snapshot_observed_at":"2026-07-02T06:56:44.796420Z","title":"Missdiff: Training dif- fusion models on tabular data with missing values","venue":null,"work_id":"283a6adc-60d8-4b48-93ce-3b7190cc6343","year":2023},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2307.00467","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:1ee020a87d5c0a41893fa25ff1beffad4c9d5d9f362549f983f326f3561f12aa","observation_id":"0c74cf3f-7a7f-413e-825e-717a79a9dc9c","resolution":{"observed_at":"2026-05-18T14:21:28.323387Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Machine learning empowering drug discovery: Applications, opportunities and challenges","venue":null,"work_id":"86fcfb2b-df56-4bd3-bec5-b05e45c24a09","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:32e3d0cf2ec5340b1a08130dbef25ed2c89a526108c2858bdbb1067b4d9555fc","observation_id":"80ab4eed-d04d-4c0b-8b34-4ac643c44f82","resolution":{"observed_at":"2026-05-18T14:21:29.110568Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Palette: Image-to-image diffusion models","venue":null,"work_id":"f4e9fa7b-fc23-444f-ac50-6d1e22715325","year":2022},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:8caea1d6da2adf16aa99cf06f66b068146a1c23627005b4609e0ee72480391aa","observation_id":"f2229533-9a29-47e9-8657-7a9d50d8a330","resolution":{"observed_at":"2026-05-18T14:21:29.115976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09258","last_updated":"2025-06-10T21:40:36Z","snapshot_observed_at":"2026-08-07T04:50:46.539816Z","submitted_at":"2025-06-10T21:40:36Z","title":"CFMI: Flow Matching for Missing Data Imputation","version":1},"cited_work":{"arxiv_id":"2506.09258","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09258","snapshot_observed_at":"2026-07-02T12:16:57.572794Z","title":"Cfmi: Flow matching for missing data imputation","venue":null,"work_id":"c7cd49a3-34e2-450c-ad50-eed73b2ece65","year":2025},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2506.09258","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:629f2fc15d0feb95ad58476f18b2834e28cf3d848800f4ac3c9423dc0b27e977","observation_id":"022b8f57-5793-4b1b-a6e8-c7207bea048f","resolution":{"observed_at":"2026-05-18T14:21:28.334740Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T14:37:16.127639Z","title":"Generative modeling by estimating gradients of the data distribution","venue":null,"work_id":"8f0fe59c-a584-44d6-a375-046f2458155c","year":2019},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:91350c7f81eeeed651fa4ca20b3ea5afbafd8ed1c30c6eaffe5ac15e0be51782","observation_id":"d0ebec2f-9e26-4cea-9021-e651cedf41aa","resolution":{"observed_at":"2026-05-18T14:21:29.107853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.13456","last_updated":"2021-02-10T18:17:04Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-11-26T19:39:10Z","title":"Score-Based Generative Modeling through Stochastic Differential Equations","version":2},"cited_work":{"arxiv_id":"2011.13456","doi":"10.1088/1748-9326/aae98d","metadata_source":"pith","pith_arxiv_id":"2011.13456","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Score-Based Generative Modeling through Stochastic Differential Equations","venue":"cs.LG","work_id":"d9110e53-a5d4-4794-a4c5-a575e91c31ad","year":2020},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2011.13456","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:fb75829d415c622e6707e02541cc78cda439a24bce61049ce6df85d3903f6dce","observation_id":"056e9594-b825-4f93-a221-cce2495ac154","resolution":{"observed_at":"2026-05-18T14:21:28.309337Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-06-01T22:58:00.812405+00:00","source":"crossref_status_cache"},{"observed_at":"2026-06-01T22:58:00.812405+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"An image inpainting technique based on the fast marching method","venue":null,"work_id":"a657ef32-e4fb-4ba1-9887-6f5750f2b308","year":2004},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:5eacf1049d1dcb62e8cab1b98d0d44dbff6da0243a5dc427a662a7d37aedb159","observation_id":"522a406b-cf71-4dfe-84aa-03847acfde03","resolution":{"observed_at":"2026-05-18T14:21:29.098705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.12171","last_updated":"2024-08-22T07:33:11Z","snapshot_observed_at":"2026-07-06T19:04:26.917233Z","submitted_at":"2024-08-22T07:33:11Z","title":"Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey","version":1},"cited_work":{"arxiv_id":"2408.12171","doi":"10.48550/arxiv.2408.12171","metadata_source":"arxiv_reference","pith_arxiv_id":"2408.12171","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Recent advances on machine learning for computational fluid dynamics: A survey.arXiv preprint arXiv:2408.12171, 2024a","venue":"arXiv (Cornell University)","work_id":"511a69ca-e0f9-439a-9d09-d84d3f8c4da7","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2408.12171","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:dff08411b5440473494f308f748ec34e392ec4d31cff99b2e42a7a671978192c","observation_id":"11dd1ce4-a1ca-497d-ab25-ac8ebabcccdd","resolution":{"observed_at":"2026-05-18T14:21:28.319110Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Restart sampling for improving generative processes","venue":null,"work_id":"ae15e2c6-6c06-4df3-8dfe-52f1f25ac737","year":2023},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:328c8c7e0a351774179875603bb264721596b2eaa2d0ac559442a8d2ff828383","observation_id":"9342046b-916a-4a96-b4e6-b38ce8e8b688","resolution":{"observed_at":"2026-05-18T14:21:29.092179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.15766","last_updated":"2024-06-02T13:55:21Z","snapshot_observed_at":"2026-07-06T18:04:54.726338Z","submitted_at":"2024-04-24T09:39:06Z","title":"Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations","version":2},"cited_work":{"arxiv_id":"2404.15766","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.15766","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Unifying bayesian flow net- works and diffusion models through stochastic differential equations","venue":null,"work_id":"d28fa240-da17-4e03-9a51-477aa38dc0de","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2404.15766","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:18f6762cf53509c67a4d72da04e78cfeea1f3514a5298721504d2d3d1bc49768","observation_id":"81d30b00-5d40-4e4f-8950-8e3f85573427","resolution":{"observed_at":"2026-05-18T14:21:28.297603Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10299","last_updated":"2024-05-18T03:46:52Z","snapshot_observed_at":"2026-08-02T07:54:35.573887Z","submitted_at":"2023-12-16T03:09:28Z","title":"Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge","version":2},"cited_work":{"arxiv_id":"2312.10299","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.10299","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Image restoration through generalized ornstein-uhlenbeck bridge","venue":null,"work_id":"d2d9dd42-160d-492d-8e5a-0d1b857fc2c0","year":2023},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"cited_paper":"/paper/2312.10299","citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:d41f752fe6f226ac973f068e7e60e30d296d92d2f6a6a7b74a7291d70714ff00","observation_id":"a83f6bc7-fe71-4547-bb44-79d35d8f1aaf","resolution":{"observed_at":"2026-05-18T14:21:28.280874Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Diffputer: Empowering diffusion models for missing data imputation","venue":null,"work_id":"d70b66c6-58d5-4b3a-adc6-769d2cfcf1be","year":2025},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:47601fcaeb8caaa3fa0028713a7e807770252d78bdf13613e826d95f29f66002","observation_id":"a4c155b2-14be-4499-80ba-a55ccdaaf462","resolution":{"observed_at":"2026-05-18T14:21:29.095414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Machine learning methods for weather forecasting: A survey","venue":null,"work_id":"c6d63cd0-ed85-47f5-81c0-1f82617a07ab","year":2025},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:981e56fc9e93064529a41eb7cf61463358c2f6d8852473398c8d6b87fd128567","observation_id":"9383e7c2-a426-4b32-a62d-2dad66e2e3d1","resolution":{"observed_at":"2026-05-18T14:21:29.101473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Improved techniques for maximum likelihood estimation for diffusion odes","venue":null,"work_id":"154f89d6-4b36-4876-965d-62ed77344d44","year":2023},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:c24509ff1069153028977db4d42f3b2e7a7be39864b209aa07ac098afc36b2d5","observation_id":"948c766a-4ac0-41e0-90ae-1e53b1a0ea0e","resolution":{"observed_at":"2026-05-18T14:21:29.127131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2409.00730","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Generating physical dynamics under priors","venue":null,"work_id":"9c3ef617-e991-4226-a1a4-13fb2be9aeb9","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:f184658983475e62c9c15571c65df2f2df66ddc2fbe8d968edc2254191f4ba52","observation_id":"b284066f-72cd-4df0-a687-7fb5c497150a","resolution":{"observed_at":"2026-05-18T14:21:28.293176Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Diffusion probabilistic fields","venue":null,"work_id":"0c094c71-9ff6-4716-bc72-e7c2b2819f16","year":2023},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:321c15eefaa9d4fd6cc1e5f49bf71a6bc3feafc31f1a14ee65784e03de76b1be","observation_id":"58c8f2bf-f7f0-4b93-8320-e540461aeada","resolution":{"observed_at":"2026-05-18T14:21:29.080798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T00:05:48.311803Z","title":"write newline","venue":null,"work_id":"8e5fda61-e601-4df4-8204-015bee341570","year":null},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:af53d9f0cbb453cead613b7700db6df6e3ca3add9a4bbdce610c62b33dca3bc8","observation_id":"176a34e5-2379-4abb-a5ea-3e711e06ffbb","resolution":{"observed_at":"2026-05-18T14:21:29.084669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T23:55:44.012295Z","title":"@esa (Ref","venue":null,"work_id":"b058608d-98d0-4821-a4ae-403d2b7cd411","year":null},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:d50be1f589026fa91393c11022af112df7a87c23282fbcd7510aef317c84036e","observation_id":"f00d2edc-d9e3-408c-87ef-1e1c01fb9a3b","resolution":{"observed_at":"2026-05-18T14:21:29.077253Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T00:05:48.337191Z","title":null,"venue":null,"work_id":"ea79bfb8-d434-45e9-8607-416d3839ec5c","year":null},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:d6702adc9b79679c435b672f920154ec30dbb81c887973d7402260e569108fed","observation_id":"40603356-4b1d-43a6-9c42-2712fb821cf2","resolution":{"observed_at":"2026-05-18T14:21:29.065923Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.ocemod.2018.09.006","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"Ocean Modelling","work_id":"839154aa-da2d-49a6-ab52-c31c28261f89","year":2024},"citing_paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","version":2},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-05-18T14:19:22.481700Z"},"links":{"citing_paper":"/paper/2509.20098"},"observation_digest":"sha256:f181eb6c4274b32027952dbc46156627ff2eed3742f1d5b163c958e5d8c2417a","observation_id":"976f4e32-648c-46f8-8061-19df496e2f55","resolution":{"observed_at":"2026-05-18T14:21:27.475986Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2509.20098","last_updated":"2026-05-01T03:44:29Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-02T20:40:54.331336Z","submitted_at":"2025-09-24T13:22:44Z","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":1,"verified_exact":16,"verified_fuzzy":37},"total_outbound_references":55},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2509.20098."}