{"as_of":"2026-08-16T18:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0681c2f720ba63cfe14ec66050ae2c7803ba8d789d96b779c4db39318ad9a4b5","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T11:20:32.843695Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/1908.09419/citation-record","integrity":"/paper/1908.09419/integrity","json":"/paper/1908.09419/citation-record.json","paper":"/paper/1908.09419"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:20:33.527407Z","title":"Tensorflow: A system for large-scale machine learning","venue":null,"work_id":"7934c917-133f-4eb9-a547-fd49d33f26d1","year":2016},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.636328Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:5d7379f50aad472fc3d1a85c7e1513c719e0d9998fa92201438d2c71035fd143","observation_id":"6f18f46f-aefd-496e-8c46-37a18b7b4ce6","resolution":{"observed_at":"2026-08-14T11:20:33.533946Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.512106Z","title":"K-subspaces with missing data","venue":null,"work_id":"bc06a237-be7d-43bf-aae5-502612f42e6b","year":2012},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.643633Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:84823ebfe4c506d886d4c76275f294d66812e07b8f688dc309313e9aef287592","observation_id":"68cd4ae9-3538-45d6-9500-d206908925d8","resolution":{"observed_at":"2026-08-14T11:20:33.516861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.496949Z","title":"Graph regularized nonnegative matrix factorization for data representation","venue":null,"work_id":"3ccc30a2-3dbd-42e5-8d75-995e287b97c1","year":2010},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.648937Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:eb9469c6208afa8dc24f6887463c873fcd24b9f48af3582b73fd77bff3e28993","observation_id":"02c437f2-7ca0-4d97-aa8e-24d20f455e87","resolution":{"observed_at":"2026-08-14T11:20:33.501925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.481514Z","title":"Subspace cluster- ing using a low-rank constrained autoencoder","venue":null,"work_id":"0bc079f9-fe1a-43b3-8c8a-a82207059e82","year":2018},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.654556Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:83cb5320d8d1f73ba3ce25ebbf9ecf5eaa21000b38fc125d34ceeff86a2a4e15","observation_id":"4da0e43f-a3f1-4a81-87e1-bd779a360daf","resolution":{"observed_at":"2026-08-14T11:20:33.486353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.465445Z","title":"Lorslim: Low rank sparse linear methods for top-n recommendations","venue":null,"work_id":"b5d85003-9725-41cf-b6b3-c810b364c466","year":2014},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.660301Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:feb94d697cd6ecf0b5ab59accad733ac2da1ec9d206bb27a8f0b98ff19b61418","observation_id":"0fd28447-a601-489a-8b6d-90990db34d61","resolution":{"observed_at":"2026-08-14T11:20:33.470519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.448535Z","title":"Sparse subspace cluster- ing","venue":null,"work_id":"63a0db3b-c005-4005-96c3-7c74dd6061a6","year":2009},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.666365Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:8ff8a86ac97abfdebca3e66699b3f8a4ff3e4ff37d7750f320c78948b2c9793c","observation_id":"949fa9ba-ee45-44d6-bfed-8e0ddd6076cb","resolution":{"observed_at":"2026-08-14T11:20:33.454347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.432278Z","title":"Sparse subspace cluster- ing: Algorithm, theory, and applications","venue":null,"work_id":"2e20f950-d693-4431-b4b3-1abe6ddf3d6c","year":2013},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.672360Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:c74c14f08fa4b305d34f573357f48a46cda9317c77f6eb2f790109a91a547706","observation_id":"7ed9dc5b-85d6-4b2a-81ae-44b8f25a24d8","resolution":{"observed_at":"2026-08-14T11:20:33.437495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.416036Z","title":"Clustering appearances of objects under varying illumination conditions","venue":null,"work_id":"44959c4f-c200-4859-b183-aadae481822e","year":null},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.677388Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:958ff01fa44361df3db207f75461a86897a759b01da7c315bc6283708490b1ce","observation_id":"83235963-d19c-4914-9452-301612fc1d07","resolution":{"observed_at":"2026-08-14T11:20:33.421115Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.401911Z","title":"Batch normalization: Accelerating deep network training by reducing internal co- variate shift","venue":null,"work_id":"18d982ac-820d-469f-83fe-a39885569c99","year":2015},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.683707Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:c2feb498809bcb2ed211e69664a14034efee69ced7d276141c7cd6f396b307bb","observation_id":"96bb7d41-a3ea-49c2-bc6f-67fa6e3829d8","resolution":{"observed_at":"2026-08-14T11:20:33.406337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.388102Z","title":"Robust multi-body feature tracker: a segmentation-free ap- proach","venue":null,"work_id":"bd1eae54-ac32-4e37-8d15-f1567338c50c","year":2016},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.688606Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:9c76d22c8038da3ef8e384c7fbd7b41ea1c0cfbb558a0afcdc01f910bd122fcd","observation_id":"bd42385f-d440-4fb8-b647-e4d79e4395cd","resolution":{"observed_at":"2026-08-14T11:20:33.392244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.374068Z","title":"Efficient dense subspace clustering","venue":null,"work_id":"a7d1cc63-4c1b-4952-8cf1-9dc565e53a86","year":2014},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.693579Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:0c3eedc0d3601d3b8d589bf96f6c213cc2daaa10b4e29c2cde097b8190a9cdca","observation_id":"2e62bec3-3f47-46e3-b60c-5035a2845c8a","resolution":{"observed_at":"2026-08-14T11:20:33.378349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.356916Z","title":"Deep subspace clustering networks","venue":null,"work_id":"19822b77-31fa-4530-9374-d945bcc02819","year":2017},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.698461Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:701a77f73e32993c955be5eab450721db798da0af20d231f67dde97f050ed865","observation_id":"16f3a7db-2233-4a66-bf06-4350b74f5d3b","resolution":{"observed_at":"2026-08-14T11:20:33.362725Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.341379Z","title":"Cluster- ing high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering","venue":null,"work_id":"8d73330c-d070-4d9c-8cf4-84f5b0d4fef3","year":null},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.703846Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:2cce2a6216dcc94658075f2cbcc0f856cfd3a9dd7cba2579acf61dc5e21c6562","observation_id":"050f263b-ae81-4914-bc4e-56b5bced9d33","resolution":{"observed_at":"2026-08-14T11:20:33.346561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.325001Z","title":"Ac- quiring linear subspaces for face recognition under variable lighting","venue":null,"work_id":"a0680fee-fed7-4786-9e99-536c5ef27d2f","year":2005},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.708669Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:fe56ce5d59a83c3b9399a24fd7f81f9ccc43f66cf42851ff49076e5c7850d1d6","observation_id":"d373e9a9-8ba7-42f3-8d5d-dd88f06ddc57","resolution":{"observed_at":"2026-08-14T11:20:33.330301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.309519Z","title":"Projective low-rank subspace clus- tering via learning deep encoder","venue":null,"work_id":"519a81ef-ca1a-4463-9254-c00b6adf86bc","year":2017},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.713308Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:b3a554157b5da4870eec26fcbf87c771f598ffe228f27444a665ee1c0e67ca01","observation_id":"0177f363-a542-4d06-86e3-f168a98f36e1","resolution":{"observed_at":"2026-08-14T11:20:33.314283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.293921Z","title":"Robust recovery of subspace structures by low-rank representation","venue":null,"work_id":"7cd3ac11-abd7-4e52-87f0-c509f5e2fdb1","year":2012},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.718637Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:5cce8ef1a6d5cb5e012eb6db24c838d371de60d710d52555261ed86b445ea48f","observation_id":"1126a2ce-8bb4-474e-a1b4-558be8b51c44","resolution":{"observed_at":"2026-08-14T11:20:33.299031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.277797Z","title":"Columbia object image library (coil-100), 1996","venue":null,"work_id":"fa8ee596-c6e0-488e-ac0d-eaaed98cf3fe","year":1996},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.722727Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:4ed2766d45d148f7b748aa65e659a317846f96085070b940c55fab36b0e1fb52","observation_id":"8f28a0f1-0bed-4867-85b7-5dded9a58f86","resolution":{"observed_at":"2026-08-14T11:20:33.283012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.261217Z","title":"On spectral clustering: Analysis and an algorithm","venue":null,"work_id":"88a669ec-0f98-4fcd-b455-01063ab1277c","year":2002},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.726933Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:2bcb29f7bb5ea12c1ef53ee238ecfc2e610f5cb720ae1cadab4c77067f6a0b00","observation_id":"7ee722b6-6dcb-4fd5-8c9e-87373ea48838","resolution":{"observed_at":"2026-08-14T11:20:33.266522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.245068Z","title":"Slim: Sparse linear meth- ods for top-n recommender systems","venue":null,"work_id":"7ba69e2f-0743-423e-b83b-8e0a4df38a99","year":2011},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.731068Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:ccc74485afe787da8f85a67d39dcabcf680ce2c4058a1f6910f6d2ce5606ffb9","observation_id":"be002f74-8650-46ca-8627-d3f86e793d69","resolution":{"observed_at":"2026-08-14T11:20:33.250190Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.227056Z","title":"Sparse linear methods with side information for top-n recommendations","venue":null,"work_id":"00546b1f-734b-4ee4-a48e-904274d0a460","year":null},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.735431Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:4bb33a00ac91faa847878adc9d413e0c0cb23d44d0ebd8f8625852e9794d8f9a","observation_id":"f6aa4f6e-c11a-4617-8ba8-9008ac75566b","resolution":{"observed_at":"2026-08-14T11:20:33.232852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.211380Z","title":"Sub- space clustering for high dimensional data: a review","venue":null,"work_id":"b4748ee7-f5bd-45f9-972b-b935d07e2d20","year":2004},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.739918Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:a3045588fd12f47b7492f0bc7f54de47bbc1d78ec4c37314a48c05688014db83","observation_id":"1a5a0be2-bf7c-4fc5-b5d8-a34a0cdbd898","resolution":{"observed_at":"2026-08-14T11:20:33.215980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.196044Z","title":"Latent space sparse and low-rank subspace clustering","venue":null,"work_id":"b180c515-8bda-4936-90c9-e33ccfb581d1","year":null},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.747828Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:7b1dee9f4e3a918816771ff02bcc8ca32c9ebfcd947ca476c34936aac2f5ccfa","observation_id":"d4c0aaa2-5888-4f13-918b-d8467ce09ea5","resolution":{"observed_at":"2026-08-14T11:20:33.200507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.179404Z","title":"Kernel sparse subspace clus- tering","venue":null,"work_id":"772a4505-01e2-41cd-becb-6fca319a2331","year":2014},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.753435Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:0e7472ef4276e63036e248ed30690ddb6efe0d030566ab8f3066686815483857","observation_id":"e9516406-cc86-444e-b144-a0e1013cebbe","resolution":{"observed_at":"2026-08-14T11:20:33.184223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.162875Z","title":"Cascade subspace clustering","venue":null,"work_id":"b738e3ef-2afe-488f-a3cc-5957133f09ca","year":2017},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.758899Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:d955abb0f2caccc238790d71124d816561fc0f59dd1fb8112cf1da0166a8a9df","observation_id":"458f2205-90f9-4f25-b0a6-af2f0c5013c7","resolution":{"observed_at":"2026-08-14T11:20:33.168668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.146636Z","title":"Structured autoencoders for sub- space clustering","venue":null,"work_id":"056822c6-db67-49c9-b2ac-f08d1c11148b","year":2018},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.763881Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:95b47842a711dbab43132077d62857005c117874843dddac47466ac26aa4ca43","observation_id":"473f1875-2af8-4f92-988f-21083a27f8bb","resolution":{"observed_at":"2026-08-14T11:20:33.152051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.130284Z","title":"Deep subspace clustering with sparsity prior","venue":null,"work_id":"deeae5f6-7c1d-4091-a3d0-aaf7e54f3345","year":2016},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.768836Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:52479faafecf746acc6088b2d0827ded8115a37a99b4a43837d5056b6280851f","observation_id":"940e9755-407b-4a54-9bc3-024f317b9303","resolution":{"observed_at":"2026-08-14T11:20:33.135363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.113917Z","title":"Mo- tion segmentation via robust subspace separation in the pres- ence of outlying, incomplete, or corrupted trajectories","venue":null,"work_id":"9ffcd87a-f8f5-44fd-878c-82365d18ad18","year":2008},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.773663Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:e3f86ed4a7b1297149e08f45f0ab6973d59c2a421eb0939863650364b532a56d","observation_id":"e66f5e77-6334-42c0-93c1-c3ef504b0bc8","resolution":{"observed_at":"2026-08-14T11:20:33.119360Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.098312Z","title":"Parameterisation of a stochastic model for human face identification","venue":null,"work_id":"af213976-2414-44f2-8f9e-f2210418c870","year":null},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.778694Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:7a4257df9c75f805a9b2a703d33181d70b8dbdf7d8eb071b3fc13852e8a477ac","observation_id":"a9a2da10-63df-426f-aa2a-cff10b69d8a0","resolution":{"observed_at":"2026-08-14T11:20:33.103315Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.083797Z","title":"Normalized cuts and image segmentation","venue":null,"work_id":"9d2faed2-acdb-41af-b710-01e918ffb503","year":2000},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.783712Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:e7c06feaca9e571d28fb867d989f2565a2c7bb66567b4dc3f1bc41a26d17d20d","observation_id":"239deccb-da83-49ad-a8e0-dfccfeb14499","resolution":{"observed_at":"2026-08-14T11:20:33.088181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.068716Z","title":"Embarrassingly shallow autoencoders for sparse data","venue":null,"work_id":"80f7cf79-3262-46eb-8b5f-dbcd182ffd9b","year":2019},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.788934Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:30976859b2b57d641bbaadb766fbf2b37560572c2cbc30968f76a5f93f227870","observation_id":"5a4f26c8-6ee9-4205-a242-b75c0556672a","resolution":{"observed_at":"2026-08-14T11:20:33.073528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.053150Z","title":"Subspace clustering","venue":null,"work_id":"c0d64b37-e36e-476b-9e7f-c64ca7e6d126","year":2011},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.793583Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:79236c2153eb39af13662a66326d57a1bb40d7b1cf19fa8104c4d03d22d99090","observation_id":"d56f7da1-2034-4790-bd73-f77c14fb2232","resolution":{"observed_at":"2026-08-14T11:20:33.058382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.036924Z","title":"Low rank subspace clustering (lrsc)","venue":null,"work_id":"9d95eae8-4c87-4365-a125-c15de6d8f08e","year":2014},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.798542Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:710f735401291197158e9cf5bfaec0d104150a2a34c2250f46acab4f9bf19cf7","observation_id":"4e708314-f4e9-442f-a405-0a8c7f804f24","resolution":{"observed_at":"2026-08-14T11:20:33.042181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.019662Z","title":"Provable sub- space clustering: When lrr meets ssc","venue":null,"work_id":"b548909f-1f34-4ac9-ba1e-5e5af1c51e89","year":2013},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.803271Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:6a5fb5ca9f3e2044120cd268dbb6f3a27d25f8d6fed840dad1e9e8ea56174967","observation_id":"415d858f-d119-4099-b895-b48c773cf07f","resolution":{"observed_at":"2026-08-14T11:20:33.025478Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:33.001204Z","title":"Unsupervised segmentation of natural images via lossy data compression","venue":null,"work_id":"c3417665-a238-4f3d-945a-7bee96afcc23","year":2008},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.808457Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:b03fa070ee975533b9cf8b9d6f305deb62b7da5a53f3faac8426b450dc7323c5","observation_id":"f2a3218f-6b37-4097-a624-e1f1eb1772fc","resolution":{"observed_at":"2026-08-14T11:20:33.006547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:32.983964Z","title":"Scalable sparse subspace clustering by orthogonal matching pursuit","venue":null,"work_id":"cea2abbf-b136-4c88-bae7-69cdc5053619","year":2016},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.813209Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:369fa5b35b4aa39ac835d88274b306d8eafd21d2dd3b9d20b28c4f4f9cda652e","observation_id":"715a00e6-0ac4-42ae-bcc8-eda915426a5b","resolution":{"observed_at":"2026-08-14T11:20:32.989442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:32.965894Z","title":"Low-rank tensor constrained multiview sub- space clustering","venue":null,"work_id":"abd6e7e1-8c6a-49ae-b9fe-ff9424ea1fe9","year":2015},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.818214Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:16de2179f58d5f1bbba22a95d87fe93fcf705f8740a27f8eaba6d0d86ed76714","observation_id":"ca71790f-658f-459f-b67b-847a869229a1","resolution":{"observed_at":"2026-08-14T11:20:32.971943Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:32.948419Z","title":"Self- supervised convolutional subspace clustering network","venue":null,"work_id":"f504981b-fe30-47b0-9b1d-3fc324fb5be3","year":2019},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.823096Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:b1b36b2697ec89c2b774c4f83bd3a795511cd160219cb289ec0a6561700b577a","observation_id":"5290ce09-951b-4dd3-8ec9-1dec99e892f0","resolution":{"observed_at":"2026-08-14T11:20:32.953669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:32.931436Z","title":"Scalable deep k-subspace clustering","venue":null,"work_id":"78f706a5-c11b-419a-a0c4-6f0a330e46c4","year":2018},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.828922Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:74de683f2ce451ee1e2c15b32982271a22a69f2864bff3edecf6fa15f4f1d4b3","observation_id":"888e0a59-e3c2-4178-8cca-70f5a6eceaf6","resolution":{"observed_at":"2026-08-14T11:20:32.936669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:32.913027Z","title":"Neural collaborative subspace clustering","venue":null,"work_id":"40b38616-3e00-4492-9338-30d02f557228","year":2019},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.833623Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:a71eae6a43dab9ef16558b4f1d7f3fab2b9d2368786f5a3bc7f08a35d25f1277","observation_id":"f001a664-a5a3-42ef-a976-7a1103c42485","resolution":{"observed_at":"2026-08-14T11:20:32.919437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:32.896558Z","title":"Latent distribution preserving deep subspace clustering","venue":null,"work_id":"3c1045e8-5fdc-46db-ae71-dddacad0985f","year":2019},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.838867Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:2bb9da7b39b9a4e9e881740840c02b90cbc053fd45fb0c6ea478fdc262e14a2c","observation_id":"b64e5aa7-be48-440b-9c1c-8dbc79c44935","resolution":{"observed_at":"2026-08-14T11:20:32.901593Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T11:20:32.876658Z","title":"Deep adversar- ial subspace clustering","venue":null,"work_id":"2ff15283-19c7-4066-a3bf-baf6be893937","year":2018},"citing_paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T11:20:32.843695Z"},"links":{"citing_paper":"/paper/1908.09419"},"observation_digest":"sha256:ff290ee838f1f8c1c9b2b2e6529bb9d025e52c59c8097a235a5333f8ebbffb3a","observation_id":"79214e79-4ad9-44a4-94ca-ed598b3e17a0","resolution":{"observed_at":"2026-08-14T11:20:32.883846Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.09419","last_updated":"2019-08-26T00:52:04Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T00:25:00.815763Z","submitted_at":"2019-08-26T00:52:04Z","title":"Deep Closed-Form Subspace Clustering"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":41},"total_outbound_references":41},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:1908.09419."}