{"as_of":"2026-08-19T20:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:223ecee34a219363f29f0cbfb06aa63eb753d25ee47da2f4a4e48e69c8546bd0","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:59:57.518117Z","state":"measured"},{"denominator":44,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":44,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.06764/citation-record","integrity":"/paper/2507.06764/integrity","json":"/paper/2507.06764/citation-record.json","paper":"/paper/2507.06764"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:00:01.683732Z","title":"Maximal sparsity with deep networks?","venue":null,"work_id":"d743bdfc-8ea1-49b6-b224-4968fc76e04b","year":2016},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:52.533692Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:6b20637cd1912eebe9b513ed5cf9b860a8dba27fa4f4c090bcd6f12f5be6fd83","observation_id":"7d1eb159-b961-4bb4-a3ee-5c4eadf35428","resolution":{"observed_at":"2026-08-06T19:00:01.688050Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.669458Z","title":"Ista-net: Interpretable optimization- inspired deep network for image compressive sensing,","venue":null,"work_id":"8c986fe0-a87c-490a-b5ea-6b17519c8980","year":2018},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:52.593993Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:7d566514a5212279215961fd7fe919c9a2bf86c57d7f90e807031b5b423a47b3","observation_id":"59754f1e-6b2a-4d89-bce3-1d8364775cd4","resolution":{"observed_at":"2026-08-06T19:00:01.674102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.653578Z","title":"Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction,","venue":null,"work_id":"a803774d-23b8-49b3-9f4c-4b25224a99a6","year":2019},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:52.703584Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:baf9e638cf71ba49cc27f70242628dad23770e89a3b99a904b5b7dc808d62f10","observation_id":"a6c78554-30f7-4d0e-8f74-c8823958820a","resolution":{"observed_at":"2026-08-06T19:00:01.657928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:52.801260Z","title":"Deep image prior,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:52.801260Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:3ed57baa0a4a57948861ef5886163ebc4afa1154f04143612253e371969e4b27","observation_id":"59f83424-e12c-4803-8969-3722c6c5db59","resolution":{"observed_at":"2026-08-06T18:59:52.801260Z","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":"2026-08-06T19:00:01.627242Z","title":"Dual-domain self-supervised learning and model adaption for deep compressive imaging,","venue":null,"work_id":"1c8e12b1-41cc-42df-aef1-785db3ad576f","year":2022},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:52.883155Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:8881ab98862188495fee9e8c8709f6a28c509b4c07ac417ca65006ecc47b67f5","observation_id":"e5d3818e-c832-4e27-b07e-99e16427a5f7","resolution":{"observed_at":"2026-08-06T19:00:01.632028Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:53.000260Z","title":"Equivariant imaging: Learning beyond the range space,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:53.000260Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:bd9cd8e26e1dc00f1089572ab051dceb5ab4791d984874ce40cc30b32a874893","observation_id":"fb051d4d-216c-4ca6-a1cd-4e65f6b1f1f4","resolution":{"observed_at":"2026-08-06T18:59:53.000260Z","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":"2026-08-06T19:00:01.601687Z","title":"Robust equivariant imaging: a fully unsupervised frame- work for learning to image from noisy and partial measurements,","venue":null,"work_id":"32998afa-130c-4f90-b35a-e63f8e405d32","year":2022},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:53.077921Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:0e3f9867f475efefa633d9d2a916829501635ca4b0118c91b8db4499e1211d34","observation_id":"097fbc89-f0b6-4810-b85e-3032c0c0a560","resolution":{"observed_at":"2026-08-06T19:00:01.606278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.586682Z","title":"Test-time fast adaptation for dynamic scene deblurring via meta-auxiliary learning,","venue":null,"work_id":"d9c772c3-c1b6-4423-aff1-9a2a8c3492c5","year":2021},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:53.190340Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:a5b60a5637dce1d9781c467e971f0b1c6ed1e1ed94d6eaa90c094a27469e3ab3","observation_id":"b7defa34-2e43-4a45-898e-9aefd78f4e93","resolution":{"observed_at":"2026-08-06T19:00:01.591581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.572575Z","title":"Fast adaptation to super-resolution networks via meta-learning,","venue":null,"work_id":"cf202c0d-8777-4f8f-87df-b522bc16fdb0","year":2020},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:53.273731Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:89b4ad4b16dbb2367c56e74b515830f789db1e1ecb2b23fabf90355005af8ef8","observation_id":"3a38ab5d-0d64-47b4-84b5-f4ed6047c974","resolution":{"observed_at":"2026-08-06T19:00:01.577114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.558789Z","title":"Test-time adaptation via orthogonal meta-learning for medical imaging,","venue":null,"work_id":"ccca2aa3-da6b-4c86-a579-34d2695e9a5a","year":2024},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:53.399923Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:c3fc06d58452ed478459f9651d1e7fe89acb816120ba9a2f297f408a88e1b637","observation_id":"35e843f0-6b39-41d1-ad99-f7483af58e2c","resolution":{"observed_at":"2026-08-06T19:00:01.563179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.544201Z","title":"Ground-truth free meta- learning for deep compressive sampling,","venue":null,"work_id":"287c9651-bb53-4472-b57d-1008b6bfa00e","year":2023},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:53.554242Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:9623481320cdc521c7e4e9244379b59d91f905035b2dcdfb75a3cffb6c11e6f2","observation_id":"64bbc96d-db91-4ef0-a973-03acaafcd7b3","resolution":{"observed_at":"2026-08-06T19:00:01.548651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.530230Z","title":"Test-time training can close the natural distribution shift performance gap in deep learning based compressed sensing,","venue":null,"work_id":"79425b99-a34b-46da-8673-dd5019d2db03","year":2022},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:53.704444Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:5240608b840fe0ac4e9deabe87c3568160ac15f47fc6c274848dcd249c738669","observation_id":"f3034284-d8bd-453d-abee-23a69db0cdfc","resolution":{"observed_at":"2026-08-06T19:00:01.534638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.516370Z","title":"Test-time model adaptation for image reconstruction using self-supervised adaptive layers,","venue":null,"work_id":"33d87c31-7bd0-4ff2-ad6c-bb0eb2910600","year":2024},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:53.861336Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:554389ad35f0b57729d1bf9e83e9eaf97959ecc8cecc553e614faba7fc5d47af","observation_id":"6d769534-de6e-4ed5-bc2a-d125a64ca620","resolution":{"observed_at":"2026-08-06T19:00:01.520817Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.501935Z","title":"Fast image recovery using variable splitting and constrained optimiza- tion,","venue":null,"work_id":"f7140252-6566-4b55-8d31-dc522c1bd80c","year":2010},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:53.983097Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:e9402825191908ef3eab5c69206ebb6f56793473fdf786ad7290156caadb0c6d","observation_id":"796990dd-65e3-43bb-8f68-f69024a0b0ac","resolution":{"observed_at":"2026-08-06T19:00:01.506304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.487640Z","title":"First-order methods of smooth convex optimization with inexact oracle,","venue":null,"work_id":"dea7f0e8-acd5-4a27-8c3b-4a57371235d0","year":2014},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:54.086110Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:fe64cc4fcf7e887158535cc7f22d5313ba62b780922ddc3e241e4c2a706aae93","observation_id":"deefae9e-9d12-4454-a13f-3adf8609e744","resolution":{"observed_at":"2026-08-06T19:00:01.491987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.472288Z","title":"Unsupervised learning from incomplete measurements for inverse problems,","venue":null,"work_id":"28a3dd7d-6180-4c76-a9f3-40a3a2f06a47","year":2022},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:54.197127Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:364c8b90cd86f7cb4b60ab83ef18652a106778a4f9143ef4e9706dab002aca51","observation_id":"f0b5cad2-01a1-41aa-bdcf-5f1356b5123e","resolution":{"observed_at":"2026-08-06T19:00:01.477619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2411.05771","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:59:57.719114Z","title":"Sketched equivariant imaging regular- ization and deep internal learning for inverse problems,","venue":null,"work_id":"685739b0-d4a2-41f2-84cf-482efa13e53c","year":2024},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:54.368784Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:0b8a995fae2c95977087791405ea0a445c4eccdb501ece6514fc926961ae36a2","observation_id":"08df344b-8eed-4425-84b4-4fbad207b72a","resolution":{"observed_at":"2026-08-06T18:59:57.810367Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.322090Z","title":"Deep unfolding network for image super-resolution,","venue":null,"work_id":"8a68ed64-f2bb-4fca-9e7b-e29fe40e960e","year":2020},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:54.542710Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:df09f5d8b9f86cd494ba0f912926d3facbf38ad4dc6d0e5886632170625ad0bf","observation_id":"16db2c30-3e42-4de3-b47b-a0fff062f3a5","resolution":{"observed_at":"2026-08-06T19:00:01.392794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.192846Z","title":"Plug-and-play admm for image restoration: Fixed-point convergence and applications,","venue":null,"work_id":"93ed053b-567b-4274-94ce-b3f92578cbe1","year":2016},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:54.678645Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:b3b43adbfaea253b1d7149bb23826183f771fc85f86c56d2ff31ba44d88b3d4f","observation_id":"64adde1f-f9da-4c24-bd8b-e93082b7ec8f","resolution":{"observed_at":"2026-08-06T19:00:01.240946Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:01.057917Z","title":"Admm-csnet: A deep learning approach for image compressive sensing,","venue":null,"work_id":"615b5424-5669-456e-80fb-9939a740a5e5","year":2018},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:54.799114Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:00a6b83415876e7256991209079ef1f9908ce9c7c211139f728d8cdbd670aa59","observation_id":"e160d7c7-897f-4c68-99ae-61aa7fa0fc47","resolution":{"observed_at":"2026-08-06T19:00:01.117294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:00.958094Z","title":"Deepred: Deep image prior powered by red,","venue":null,"work_id":"e7a029ac-f534-4ff8-9ef2-41c36058c0bc","year":2019},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:54.966455Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:6d3eceb816b74d89ccc3540e20f86db57a72217d4f6662f997ffc91ac1c0ce5e","observation_id":"5ffb80da-4de4-44de-a54c-f09514d98249","resolution":{"observed_at":"2026-08-06T19:00:00.997273Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:00.922372Z","title":"Self- supervised deep unrolled reconstruction using regularization by denoising,","venue":null,"work_id":"d59c9f01-14f0-4a36-b6bc-946d70e0e6a8","year":2023},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:55.121689Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:eb671132dac9f2d121feffd0d5d5efb8fc121400d01b736065f801572cf1ab5c","observation_id":"b211125e-9f26-4149-a785-0e2b10a799fe","resolution":{"observed_at":"2026-08-06T19:00:00.947241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.09327","last_updated":"2024-11-19T21:51:34Z","snapshot_observed_at":"2026-08-16T14:09:51.677952Z","submitted_at":"2024-03-14T12:17:07Z","title":"Perspective-Equivariance for Unsupervised Imaging with Camera Geometry","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.09327","snapshot_observed_at":"2026-08-06T18:59:55.296794Z","title":"Perspective-equivariant imaging: an unsupervised framework for multispectral pansharpening,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:55.296794Z"},"links":{"cited_paper":"/paper/2403.09327","citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:bdc5687d12715b88030e99ef485918e79c7b66e1d6d36c5620dfd1e1d3fa90f5","observation_id":"2a243864-a259-4ee8-b86e-eae02f157fec","resolution":{"observed_at":"2026-08-06T18:59:55.296794Z","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":"2026-08-06T19:00:00.493223Z","title":"Equivari- ant plug-and-play image reconstruction,","venue":null,"work_id":"6c74aa66-3a03-4c6a-8f9d-7aac7e8c9592","year":2024},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:55.403277Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:429d95fed6103411f5d803c2b672600ce67f30e5478a79ce26cd83e7a07e74f4","observation_id":"70001950-8e7c-4b11-a300-bdbe703436e6","resolution":{"observed_at":"2026-08-06T19:00:00.750963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:00.375688Z","title":"Algorithm unrolling: Inter- pretable, efficient deep learning for signal and image processing,","venue":null,"work_id":"aaf4ba13-5ae5-4da6-bf4b-cc6b5183974d","year":2021},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:55.483186Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:9de648bf604a414dca64f43ab46069454e385e28250fe07959ede5b81322e22e","observation_id":"2f47986b-9096-4860-842c-681347a402bd","resolution":{"observed_at":"2026-08-06T19:00:00.402911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:00.252453Z","title":"Deep unrolling networks with recurrent momentum acceleration for nonlinear inverse prob- lems,","venue":null,"work_id":"613401c8-e8f9-4356-a29f-b5a1244b2c82","year":2024},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:55.654080Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:7f5f66caa42a5a5fb046eeb0e41b723c8190861dd810503c5b69dfd88a6e29bd","observation_id":"fb97df19-994f-4866-abbb-62e48d2d9638","resolution":{"observed_at":"2026-08-06T19:00:00.309675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:00.133391Z","title":"Linearized augmented lagrangian and alternating direction methods for nuclear norm minimization,","venue":null,"work_id":"e6d3cd14-4703-4e5b-a9ce-37909c0daa74","year":2013},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:55.770080Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:533e13c4dddaa9d54d398395e20e16d025d386b569066091b9af0c07ff658515","observation_id":"478ce839-8c46-4696-9bbc-b5fa9560b418","resolution":{"observed_at":"2026-08-06T19:00:00.191063Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T19:00:00.019094Z","title":"Inexact half-quadratic opti- mization for linear inverse problems,","venue":null,"work_id":"f7e7f0c2-6f65-404e-b202-e807e444ec44","year":2018},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:55.883168Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:73f62e8d41222d14ca7dd2cb5db950834f16551bdaa91ff325f20cca39d29126","observation_id":"d54c24bf-9a9b-4015-b047-e6d140d415d7","resolution":{"observed_at":"2026-08-06T19:00:00.069217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:59.904400Z","title":"Inexact half-quadratic optimization for image reconstruction,","venue":null,"work_id":"952b98e0-8bef-478e-8ea3-8a06af00435a","year":2016},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:56.027369Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:96ca7ec6ca567e4b92bd31bff83f8b916e75858dac2d98b5a4ac735bd3aaa78b","observation_id":"109f2828-2e37-4ac2-80ce-7c74b14b76a2","resolution":{"observed_at":"2026-08-06T18:59:59.961911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:59.791541Z","title":"Proximal alternating lin- earized minimization for nonconvex and nonsmooth problems,","venue":null,"work_id":"0fedba62-31ff-4b30-9d38-d797d13fd2d4","year":2014},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:56.152359Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:215250e134fe3529d1085fa5c8ef047152e879b3c4b53e561eac86c186464eb2","observation_id":"b18a603e-5f0e-4933-96f0-0f027e1093c5","resolution":{"observed_at":"2026-08-06T18:59:59.846085Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:59.680266Z","title":"Inexact block coordinate descent algorithms for nonsmooth nonconvex optimization,","venue":null,"work_id":"131136b1-5cd0-4164-b01e-3d9ca35001e8","year":2019},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:56.275838Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:dd8477e9c2a50a3fdcd679951b338515f1bc5cdb517c908031c45d2245ef5488","observation_id":"e769a686-2a2e-4a65-aef7-81ac513d780c","resolution":{"observed_at":"2026-08-06T18:59:59.736195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:59.583832Z","title":"A method of solving a convex programming problem with convergence rate o (1/k2),","venue":null,"work_id":"56dfe7c2-5b81-46e8-8b50-ec13b00c1971","year":1983},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:56.426525Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:4a7156b712783ebd830b0f3cd3fa24dabfc99b8f2241d9c5a9e893c6c2eb50b8","observation_id":"b1a0e396-aaec-4dc2-a5f4-835b164d318a","resolution":{"observed_at":"2026-08-06T18:59:59.634918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:59.471873Z","title":"Gradient methods for minimizing composite objective func- tion,","venue":null,"work_id":"5b8660a9-3541-438b-a918-1cbe3bad0bcf","year":2007},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:56.474329Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:e8f274c18f9eefdf0cf569077fe382400774a603f3694b90772ad544ea18098a","observation_id":"25b1621a-34cd-4ddc-8609-f8c0e58fbacf","resolution":{"observed_at":"2026-08-06T18:59:59.519703Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:59.376390Z","title":"A guide to stochastic optimisation for large-scale inverse problems,","venue":null,"work_id":"69dddace-7b77-43ac-87fb-e051ba0f2a67","year":2025},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:56.565428Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:65e5a872e0c2157694bf6b3eaca53cd80c9803d9dacee17809c930fc34266750","observation_id":"6732526c-6398-4990-8ace-4632d97ff569","resolution":{"observed_at":"2026-08-06T18:59:59.414839Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:59.270022Z","title":"Provably convergent plug-and-play quasi-newton methods,","venue":null,"work_id":"27a28eec-eef2-48f1-9e80-039354828b52","year":2024},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:56.694620Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:76730dce94e382d8ffb028381e9e6cbb2282e253cea2d250c7c9d19774d00350","observation_id":"f1ab004e-ae33-4518-9d31-17660af6babf","resolution":{"observed_at":"2026-08-06T18:59:59.314276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:59.162710Z","title":"Plug-and- play priors for model based reconstruction,","venue":null,"work_id":"617f359f-ffeb-4352-aa13-2a8c23ea4ab5","year":2013},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:56.796273Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:46faa49b574eda932d5f9db163b59f97ae6ea85d9e7a50c15fa2085ea7301a20","observation_id":"793aec9b-5bf8-4c87-bc0f-67c506997cbf","resolution":{"observed_at":"2026-08-06T18:59:59.219150Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:58.987287Z","title":"Image de- noising by sparse 3-d transform-domain collaborative filtering","venue":null,"work_id":"54d8fca2-7ef7-4c61-b17a-9e415ed5a9b6","year":2007},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:56.904677Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:f7b5bf3d9843ea5fd18bc822a6e4fa745a0003a8adaffda94f15bcfb7e8bd76c","observation_id":"095ea164-26b4-4475-9a4a-bb046d6f0838","resolution":{"observed_at":"2026-08-06T18:59:59.067305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:58.805413Z","title":"Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising,","venue":null,"work_id":"0c75502b-c676-4887-b54a-d0dbd944bfc6","year":2017},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:57.008445Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:7c8542a65b3d40525b3f3cb364ab21b5bbe376db8fb6c44df5e05871a99eee33","observation_id":"1555b8c4-65c2-4692-8397-219580a2052f","resolution":{"observed_at":"2026-08-06T18:59:58.888849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:58.618304Z","title":"Truly shift-equivariant convolu- tional neural networks with adaptive polyphase upsampling,","venue":null,"work_id":"70d05e5d-ed9e-4531-9735-684b95646de6","year":2021},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:57.087289Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:f5c44641ef9a4d2f6afa5210f3ba12152c02bb9da4835574c986bb17d81e9e6f","observation_id":"1131ff63-f015-4f74-a8ad-c8bd50cba672","resolution":{"observed_at":"2026-08-06T18:59:58.726314Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:58.499568Z","title":"U-net: Convolutional networks for biomedical image segmentation,","venue":null,"work_id":"30f33568-c555-4045-952f-314b3c9a2eb1","year":2015},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:57.168300Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:51e7919e50926c10634909b3b06d9dc8e77256f30fed7d245f4f72bcf2325108","observation_id":"b8c4f0a7-2782-4592-ba76-17b635180e94","resolution":{"observed_at":"2026-08-06T18:59:58.552796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:58.336489Z","title":"A plug-and-play deep image prior,","venue":null,"work_id":"e733cbba-b6e2-4f13-aa8b-1e994e13300e","year":2021},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:57.255648Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:a3f79be1db928c497cb649042a0d78641ff09991aa58e12737357309d1b0bcd7","observation_id":"78c3e469-338a-4208-915b-5812b538dfd2","resolution":{"observed_at":"2026-08-06T18:59:58.411237Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:58.172555Z","title":"The cancer imag- ing archive (tcia): maintaining and operating a public information repository,","venue":null,"work_id":"a2843e74-ad60-42e1-b3ba-79f90e7a15d0","year":2013},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:57.368920Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:3436de9acaabd07beb4641188638801dee998cc8e87d8c29049656ce728dfd0b","observation_id":"002f9427-11b7-4889-84e2-73ddec4d1fec","resolution":{"observed_at":"2026-08-06T18:59:58.243166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T18:59:57.919026Z","title":"Single image super- resolution from transformed self-exemplars,","venue":null,"work_id":"ac692e2e-823b-42a2-af96-da997b2c22af","year":2015},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:57.439965Z"},"links":{"citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:81a1362812dc289477c7cdaf94392406795b423afd94077d22add8e186152f78","observation_id":"91795492-4652-434c-82e8-9bf1461050f9","resolution":{"observed_at":"2026-08-06T18:59:58.040691Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.01985","last_updated":"2025-02-11T18:09:35Z","snapshot_observed_at":"2026-08-16T13:21:43.456523Z","submitted_at":"2024-09-03T15:26:51Z","title":"UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.01985","snapshot_observed_at":"2026-08-06T18:59:57.518117Z","title":"Unsure: Unknown noise level stein’s unbiased risk estimator,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting","version":5},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T18:59:57.518117Z"},"links":{"cited_paper":"/paper/2409.01985","citing_paper":"/paper/2507.06764"},"observation_digest":"sha256:8d13d63df203073912d0c21d9755eae4d5afbd29fd8c55717bf3f9a068ec2cb3","observation_id":"13f94960-4ea6-4b20-baac-becfb9bca1fa","resolution":{"observed_at":"2026-08-06T18:59:57.518117Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.06764","last_updated":"2026-06-27T18:24:56Z","latest_version":5,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-12T00:32:26.487533Z","submitted_at":"2025-07-09T11:47:06Z","title":"Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":1,"verified_fuzzy":39},"total_outbound_references":44},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2507.06764."}