{"as_of":"2026-08-17T05:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2740135b2d62d8ac3c837d8e2b9829259de9a32c5207bef67d68c26f51fe821f","coverage":[{"denominator":49,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T13:14:14.203844Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"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/1908.05783/citation-record","integrity":"/paper/1908.05783/integrity","json":"/paper/1908.05783/citation-record.json","paper":"/paper/1908.05783"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:14:15.015282Z","title":"IEEE Trans","venue":null,"work_id":"7748d6f7-5826-46eb-915d-7b8947cf2b6c","year":2013},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:13.969342Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:929e2f311004bc303601cd18436be4d29ddebc6cb2588850fd14e9125d1c5843","observation_id":"7db42ae4-bf97-48bf-b484-a8447338648a","resolution":{"observed_at":"2026-08-14T13:14:15.020081Z","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":"2026-08-14T13:14:14.999628Z","title":"Springer-Verlag, Berlin, Heidelberg (1990)","venue":null,"work_id":"e098137c-20c8-49b0-b146-53d112d274de","year":1990},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:13.975791Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:a52af26de3d1fa8a520f9a09a816fdfd2d3ee880366c83e4dd90fbba619ba28c","observation_id":"9c2123ab-9b02-4208-ae71-055986396627","resolution":{"observed_at":"2026-08-14T13:14:15.004618Z","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":{"arxiv_id":"2003.14263","last_updated":"2020-04-06T11:16:10Z","snapshot_observed_at":"2026-08-17T04:06:19.765330Z","submitted_at":"2020-03-31T14:48:36Z","title":"A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set","version":2},"cited_work":{"arxiv_id":"2003.14263","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.14263","snapshot_observed_at":"2026-08-14T13:14:14.379298Z","title":"A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set","venue":"stat.ML","work_id":"78d759e3-7fea-47b1-bb2e-5cb9a3dc8e05","year":2020},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:13.980720Z"},"links":{"cited_paper":"/paper/2003.14263","citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:df7b65cd7e2b4c812c4ad26dfba25fffbc034fdfe6aece653392e36b2267c0d9","observation_id":"b31b888f-277d-4b47-bdc0-6ce73c6f3727","resolution":{"observed_at":"2026-08-14T13:14:14.384460Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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":"2026-08-14T13:14:14.983433Z","title":null,"venue":null,"work_id":"c6044eb3-82f7-4d2d-bc14-2c9e6e56441a","year":1998},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:13.985854Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:beac2f253f936e246ebccf0794b0455e1b5f358e074188cc35fb0a607b479976","observation_id":"47038e83-c21a-422d-8cdb-4cf72b41faea","resolution":{"observed_at":"2026-08-14T13:14:14.989067Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-14T13:14:14.968357Z","title":"In: Proceedings of the 1st Conference on Fairness, Accountability and Transparency, Proceedings of Machine Learning Research, vol","venue":null,"work_id":"b8763930-eaf1-479e-8af1-02b2b02439d9","year":2018},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:13.990670Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:3a900254f3dd724996a03f2419af8e3009259d888707b133c8061a8ca2dc95a8","observation_id":"2363ddd9-106a-43fd-8ad6-45a5a86c2c5a","resolution":{"observed_at":"2026-08-14T13:14:14.973236Z","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":"2026-08-14T13:14:14.952218Z","title":"Big data 5, 153–163 (2017) 14 Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 RegularizationA PREPRINT","venue":null,"work_id":"d405f6b7-d7f6-43fa-a4ba-e012298a64a2","year":2017},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:13.995948Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:4c9855d68c6cc33aa593959e7ab6a7c7744c4c5fdd8d664be1a8972b1a9380db","observation_id":"439af4e6-2840-4802-bd89-280d5d132b18","resolution":{"observed_at":"2026-08-14T13:14:14.957765Z","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":"2026-08-14T13:14:14.936491Z","title":"In: Proceedings of the 27th International Conference on Neural Information Processing Systems - V olume 2, p","venue":null,"work_id":"1ae00e27-e2b3-47f6-aade-49042d54c230","year":2014},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.001648Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:6d410909be93c8c76932be6d8802aa965868c835e8174740824f945aef6a0525","observation_id":"436539ef-afb0-4d64-b048-d57e1a8cfd68","resolution":{"observed_at":"2026-08-14T13:14:14.941136Z","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":{"arxiv_id":"1806.03195","last_updated":"2018-07-18T07:09:46Z","snapshot_observed_at":"2026-08-15T01:08:11.650607Z","submitted_at":"2018-06-08T14:42:29Z","title":"Obtaining fairness using optimal transport theory","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.03195","snapshot_observed_at":"2026-08-14T13:14:14.006256Z","title":"arXiv preprint arXiv:1806.03195 (2018)","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.006256Z"},"links":{"cited_paper":"/paper/1806.03195","citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:909370fc3f175eec228d1061021e5ac4dbf650f1e6e91c3aab48d5e4993c00b0","observation_id":"9642ad27-a0a3-4af0-84e0-ac63fd8ee4e8","resolution":{"observed_at":"2026-08-14T13:14:14.006256Z","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":"2026-08-14T13:14:14.921986Z","title":"Information and Inference: A Journal of the IMA (2018)","venue":null,"work_id":"e79a2073-485c-4417-8f10-b2fc104e8b95","year":2018},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.011058Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:921345a659cd04e5df8d52b639d8912ad55f0b8a0e3178c3bbe1f800e8df798a","observation_id":"7d58f524-7b52-4c52-974c-7e9e9b15b3b5","resolution":{"observed_at":"2026-08-14T13:14:14.926491Z","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":{"arxiv_id":"2005.13755","last_updated":"2020-05-26T11:40:13Z","snapshot_observed_at":"2026-08-12T03:49:51.339779Z","submitted_at":"2020-05-26T11:40:13Z","title":"Review of Mathematical frameworks for Fairness in Machine Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.13755","snapshot_observed_at":"2026-08-14T13:14:14.015629Z","title":"arXiv preprint arXiv:2005.13755 (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.015629Z"},"links":{"cited_paper":"/paper/2005.13755","citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:def61aef26d535b82786490b455693d4c60570d32aa5ea67845aa95a4f6c055a","observation_id":"89233410-3af1-4ba2-adff-cd5268ec0188","resolution":{"observed_at":"2026-08-14T13:14:14.015629Z","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":"2026-08-14T13:14:14.906926Z","title":null,"venue":null,"work_id":"ed695678-d815-427d-8b22-3f0cebe139e6","year":2011},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.020952Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:e28b18da9543009253e6460d1d292d7f8f09548554e193f2904c3110bab8f59d","observation_id":"b61731c8-2623-4939-9012-388c9ada1201","resolution":{"observed_at":"2026-08-14T13:14:14.912003Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-14T13:14:14.891013Z","title":"In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp","venue":null,"work_id":"702658f5-957b-485a-99d3-b898b4f80e3d","year":2015},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.025906Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:f5ef2c0d2bcf37a4ac5a91a0156362dff16bdd4560826ae12e4a2cfde368c571","observation_id":"21b2b105-7dfe-4177-801d-223a29d87327","resolution":{"observed_at":"2026-08-14T13:14:14.896077Z","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":"2026-08-14T13:14:14.873416Z","title":"In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, p","venue":null,"work_id":"0a07b096-b2a2-43fe-9d10-fb6c72185291","year":2015},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.030712Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:a1c19216eecec5045788a32d926f3753d4af5ff4f202eecf42457346d3285613","observation_id":"f3e76da6-233f-45b5-b5c8-226ea19731e1","resolution":{"observed_at":"2026-08-14T13:14:14.879026Z","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":"2026-08-14T13:14:14.857248Z","title":"In: International Conference on Machine Learning, pp","venue":null,"work_id":"03b4b949-7bb6-42d4-aaf7-c2b3d40b2f94","year":2019},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.035334Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:c289f2e7ce9610c3c38b8510892c433ff45da059b28b833fb3106a1e7645df30","observation_id":"79f994db-7628-4048-8eaa-a22454047766","resolution":{"observed_at":"2026-08-14T13:14:14.862138Z","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":"2026-08-14T13:14:14.841677Z","title":null,"venue":null,"work_id":"6546458f-08a1-479a-b4c9-ace515ee3053","year":2016},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.039982Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:115975ab37189af435c83005e20cb51d312cbe53df61788f1c9812eddb3bbfd3","observation_id":"37ee4b5c-8bbd-4bda-ac2b-6fdd436b4e55","resolution":{"observed_at":"2026-08-14T13:14:14.846468Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-14T13:14:14.826007Z","title":"In: Advances in neural information processing systems, pp","venue":null,"work_id":"185740d1-cf41-4c1f-814e-588d1ed23163","year":2016},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.044580Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:653ce8d3432cb66dd8ca1be8cfcb950dfc148c4d80e6baa38c321bcc15eeb270","observation_id":"c36f205f-24cf-4949-a9b6-c2638af99adf","resolution":{"observed_at":"2026-08-14T13:14:14.831586Z","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":"2026-08-14T13:14:14.810104Z","title":"In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":"ccbb18bd-17c9-4032-b8bf-2af9270e2f13","year":2016},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.049361Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:849b62004b6987feb1d5d58fe35a29b9750c76478b2e197349f28961e8299e8f","observation_id":"fe8581f7-2d58-4d97-a2cc-6b305f7d1af0","resolution":{"observed_at":"2026-08-14T13:14:14.815209Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:14:14.054155Z","title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.054155Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:59f14476d0facf21dee1dbc7d97264c535525a40b9a323cc1b6d08ea8784acc5","observation_id":"d8768c70-cbe5-4cf1-a80b-49c6ea87c20a","resolution":{"observed_at":"2026-08-14T13:14:14.054155Z","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":"2026-08-14T13:14:14.781742Z","title":"In: International Conference on Machine Learning, pp","venue":null,"work_id":"b1dc378a-c32b-42dd-a46a-e985970832dc","year":2018},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.058896Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:e8ce5a6de16160eb6cee389df5ec5c75f2ccb5c98b8e296f434c0bd75ace0bba","observation_id":"37a5c181-7232-4af8-9922-60044053ec6c","resolution":{"observed_at":"2026-08-14T13:14:14.787958Z","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":"2026-08-14T13:14:14.764657Z","title":"In: Proc","venue":null,"work_id":"a844f8b3-2bb3-45e4-a67c-f911dcda3196","year":2019},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.063721Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:ca9c6e047c6706cb8d0a5630d9afb5ab40ba153c092c8840370ba6c329acb589","observation_id":"1f99bd03-c3e9-429f-9795-c1c4d38bea9c","resolution":{"observed_at":"2026-08-14T13:14:14.769916Z","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":"2026-08-14T13:14:14.749602Z","title":"In: Proceedings Conference on Uncertainty in Artificial Intelligence (UAI) (2019)","venue":null,"work_id":"76b6d5e4-5186-4eab-b7c7-85774d449e12","year":2019},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.068872Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:6476865a6dd24ffecee4fa525dcd492a1842ae175fa4d13d407919acf0772549","observation_id":"8ff9da66-36cf-478e-8a28-74edd79cc7f0","resolution":{"observed_at":"2026-08-14T13:14:14.754513Z","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":"2026-08-14T13:14:14.733825Z","title":null,"venue":null,"work_id":"7cead3a1-1c81-4fee-9248-585b63a9222c","year":2019},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.073646Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:78a06f1b87ef7d6f2f252a6280256b3c87781bddc4025c70febcdb2ed8e13c1f","observation_id":"13db1976-9309-4d8d-ac78-0948f51d7026","resolution":{"observed_at":"2026-08-14T13:14:14.738784Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-14T13:14:14.717179Z","title":"In: Proceedings of the 2012th European Conference on Machine Learning and Knowledge Discovery in Databases - V olume Part II, p","venue":null,"work_id":"94544a5a-4eb4-4a63-a918-225109119b2f","year":2012},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.078327Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:d68a7b7a2f632c55e08472238bd3c2444b1a17e360b67ae33594d5880b1e1ea2","observation_id":"b3e04001-0975-4c0a-b831-ccc42ee24ebb","resolution":{"observed_at":"2026-08-14T13:14:14.722488Z","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":"2026-08-14T13:14:14.701360Z","title":"In: International Conference on Machine Learning, pp","venue":null,"work_id":"a3126419-aa38-4394-bd62-6eb8a5e78950","year":2018},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.083159Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:a47a33b5916f3470340ab9182a0d3975e55c2c2e095f56ef5eb2338d5d141026","observation_id":"6c4783a0-ac15-490f-a912-94d0fb3c6511","resolution":{"observed_at":"2026-08-14T13:14:14.706128Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:14:14.087940Z","title":"International Conference on Learning Representations (2014)","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.087940Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:5adfaa554b45bc9e0c5712c8d64661f143a3d103f3f89b1ed4e69ec3e32cc1b5","observation_id":"0c7c4344-461c-469a-9481-16741feecf8c","resolution":{"observed_at":"2026-08-14T13:14:14.087940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-14T18:51:16.666127Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-14T13:14:14.092546Z","title":"CoRR abs/1412.6980 (2014)","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.092546Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:273ec87001208c9772892b6d1ffc12d639df62712e48ddc9575854d3e51ed0a8","observation_id":"44d7de79-775d-474c-8ca9-aaaf04efa7d6","resolution":{"observed_at":"2026-08-14T13:14:14.092546Z","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":"2026-08-14T13:14:14.673443Z","title":null,"venue":null,"work_id":"77eac564-01a4-44f1-8133-49550c3ff0b0","year":2017},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.097137Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:83e6583d97f59badc13a776f30ae029d78c608aee895c3091197e31fd6889fb4","observation_id":"6bb25d64-1e16-40db-9fb4-75227aae7697","resolution":{"observed_at":"2026-08-14T13:14:14.678963Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-14T13:14:14.657819Z","title":"In: Advances in Neural Information Processing Systems 25, pp","venue":null,"work_id":"e4114098-4f2e-4a47-8698-9c534d138795","year":2012},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.101997Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:d0edd885a5808ea112a7b2d4d82002949d76157ff60124cad6f650f6eacd985e","observation_id":"348732aa-537b-412e-a8d5-7c3dfa5af11d","resolution":{"observed_at":"2026-08-14T13:14:14.663335Z","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":"2026-08-14T13:14:14.642674Z","title":null,"venue":null,"work_id":"0e61aca6-1cbc-41cf-bb2b-86dd63870276","year":2017},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.106709Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:2d2d36ed51727f78df3a1417ff396085053bc58f7f9be1e4c8b0e06874ad0143","observation_id":"273127c7-52ff-4f5f-8bab-217b1ebcbc17","resolution":{"observed_at":"2026-08-14T13:14:14.647449Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-14T13:14:14.626064Z","title":"Neural Comput","venue":null,"work_id":"0551b797-aacc-40cc-93e3-558e5e05d00f","year":1989},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.111260Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:e8d6c0e32dfd48657d98817ab86a9283d61dd04e8e8c4ed44034310328f370d9","observation_id":"38fb89ce-db51-44e6-b981-aaf1b12c4227","resolution":{"observed_at":"2026-08-14T13:14:14.631961Z","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":"2026-08-14T13:14:14.609792Z","title":"In: Proceedings of the IEEE, vol","venue":null,"work_id":"490ebd4e-614f-41ec-9e33-2046ded31ae0","year":1998},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.116163Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:c017a0609062beb9e2d964970e1f809f3ea059e163090b9a978d590e66a3961f","observation_id":"8dd65c40-93de-40e4-b828-30a0a8311b2d","resolution":{"observed_at":"2026-08-14T13:14:14.614699Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:14:14.120693Z","title":"In: Proceedings of International Conference on Computer Vision (ICCV) (2015)","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.120693Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:e2d060dfff15bdcd7f43ba654c73b037fe52da296e84f62f30a436bac6a56cfc","observation_id":"626f93d0-7bd3-41e4-8bb2-4f7d3944661d","resolution":{"observed_at":"2026-08-14T13:14:14.120693Z","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":"2026-08-14T13:14:14.583392Z","title":"Information and Inference: A Journal of the IMA (2019)","venue":null,"work_id":"d8dc8a9f-695b-4fbc-bc13-8862c741550d","year":2019},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.125710Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:fc9a66ab56123498c67dccf61a7f6557ca98715f2712b99485dcd53288a87be2","observation_id":"20fadf25-5f59-41d3-8958-a118e1bb680f","resolution":{"observed_at":"2026-08-14T13:14:14.588912Z","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":{"arxiv_id":"1811.00247","last_updated":"2020-05-07T06:17:20Z","snapshot_observed_at":"2026-08-14T18:05:54.771633Z","submitted_at":"2018-11-01T05:49:40Z","title":"FNNC: Achieving Fairness through Neural Networks","version":3},"cited_work":{"arxiv_id":"1811.00247","doi":null,"metadata_source":"pith","pith_arxiv_id":"1811.00247","snapshot_observed_at":"2026-08-14T13:14:14.308919Z","title":"FNNC: Achieving Fairness through Neural Networks","venue":"cs.LG","work_id":"78e13d16-8036-4dc2-8afb-5498cda8e293","year":2018},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.130685Z"},"links":{"cited_paper":"/paper/1811.00247","citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:84fde0f66852eaa479e8746561ba34060521b5b4a410cffea64595b076a55ca6","observation_id":"7fdd91b4-9833-48a1-8479-27285cf4ff24","resolution":{"observed_at":"2026-08-14T13:14:14.315433Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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":"2026-08-14T13:14:14.566902Z","title":"In: Proceedings of the 36th International Conference on Machine Learning, vol","venue":null,"work_id":"d96c9f40-f6c7-41e3-8da8-8df610d13e02","year":2019},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.135751Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:4ea11b14769243b86e67031f32b7d46cf908e126251fb1a72f3289322f86c344","observation_id":"9eaf588c-f3b0-47d4-bc11-cc80d832cb3c","resolution":{"observed_at":"2026-08-14T13:14:14.572268Z","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":"2026-08-14T13:14:14.551894Z","title":"University of California Press (2016)","venue":null,"work_id":"03982c9d-3571-467d-b6be-a5bebab28fff","year":2016},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.140716Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:cf07d611571c83410ae4b5e8a50262e0c81eba6444c2eab5b280705804f37b08","observation_id":"01e044ae-1da2-44d6-8206-7c407478cb3a","resolution":{"observed_at":"2026-08-14T13:14:14.556683Z","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":{"arxiv_id":"1907.11569","last_updated":"2020-12-01T16:02:49Z","snapshot_observed_at":"2026-08-14T16:01:58.750576Z","submitted_at":"2019-07-26T13:30:02Z","title":"Making Neural Networks FAIR","version":4},"cited_work":{"arxiv_id":"1907.11569","doi":null,"metadata_source":"pith","pith_arxiv_id":"1907.11569","snapshot_observed_at":"2026-08-14T13:14:14.285670Z","title":"Making Neural Networks FAIR","venue":"cs.LG","work_id":"8a7bd6c0-f672-47d3-9a22-371e9fc6d145","year":2019},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.145462Z"},"links":{"cited_paper":"/paper/1907.11569","citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:9a3796b1107933d9abe3bc3e0c926ba898c49c3d73ae71d2cf14806802f0b5de","observation_id":"00f5f38f-9eae-4965-b1ed-c3424b78be7d","resolution":{"observed_at":"2026-08-14T13:14:14.290548Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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":"2026-08-14T13:14:14.536110Z","title":"In: Recent Trends in Learning From Data, pp","venue":null,"work_id":"3f2abf7f-d103-4d3c-880e-939fb32a33d8","year":2020},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.150286Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:49a05de090b3050dde92b4fa113f441e74064bf56c6c989e311f4ab4eeada0ad","observation_id":"bbe9d348-eab1-4a5f-ae6b-183653e1ee22","resolution":{"observed_at":"2026-08-14T13:14:14.541458Z","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":"2026-08-14T13:14:14.521841Z","title":"In: ECML/PKDD (1), pp","venue":null,"work_id":"e2f45cd6-213d-470a-adab-d8700eaecd7a","year":2017},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.155533Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:8775c6991dea834b6d1ac77bda75fb57a0eb1ebcd456b38a5e886679a60cf4cc","observation_id":"1d388b9b-163b-49ad-b17b-53241e3dfd91","resolution":{"observed_at":"2026-08-14T13:14:14.526399Z","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":"2026-08-14T13:14:14.506326Z","title":"In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)","venue":null,"work_id":"d1b8b5a0-bbc0-4543-8dc0-d56387806dd0","year":2019},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.160506Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:cb72606d0092edbf53c050338704f487e1223aebd7eef4a9217de01414d615ce","observation_id":"88dffef4-f8be-463c-b260-2f11200530cc","resolution":{"observed_at":"2026-08-14T13:14:14.511634Z","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":"2026-08-14T13:14:14.490726Z","title":null,"venue":null,"work_id":"86cbf60d-5aa6-43a6-9538-942e8933954e","year":2018},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.165539Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:b2cc71aafd7654c5d98304a3d470f987a651889d8aa0696197b83bbf0a7a1e9f","observation_id":"cbcaef91-b420-4314-ac98-41bcee0f845b","resolution":{"observed_at":"2026-08-14T13:14:14.495399Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-14T13:14:14.474956Z","title":"In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp","venue":null,"work_id":"34722f18-98ab-45b4-95a2-80bd764be213","year":2016},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.170076Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:ec290090da822499a53866eecebca17739fa25fe203ba21e0e7141e0e82e06fb","observation_id":"cc2cd1dd-1678-469f-b52c-eaa6e796fd9a","resolution":{"observed_at":"2026-08-14T13:14:14.480214Z","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":{"arxiv_id":"1801.06229","last_updated":"2020-05-08T18:50:04Z","snapshot_observed_at":"2026-08-14T19:53:56.595790Z","submitted_at":"2018-01-18T20:32:09Z","title":"Anchor regression: heterogeneous data meets causality","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.06229","snapshot_observed_at":"2026-08-14T13:14:14.174591Z","title":"arXiv preprint arXiv:1801.06229 (2018)","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.174591Z"},"links":{"cited_paper":"/paper/1801.06229","citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:55ea755cbd283bda60cd1c028afbb5d12c0ce2c692081963978406c9c2909b33","observation_id":"c3fce08c-cdcc-4df6-813a-e2ae7f657f36","resolution":{"observed_at":"2026-08-14T13:14:14.174591Z","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":"2026-08-14T13:14:14.457407Z","title":null,"venue":null,"work_id":"a42bc0d3-30d0-46ae-918b-72623590703d","year":1988},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.180011Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:b4b3dba5cc63957323de5e1877ff2e764b29f9b992106bc3f7367eb73feb4354","observation_id":"f4525e4a-9e7a-4487-bfd5-0ecb06e695a6","resolution":{"observed_at":"2026-08-14T13:14:14.462865Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-14T13:14:14.441796Z","title":null,"venue":null,"work_id":"621c34f1-3b6f-4b0d-a671-78dab9b78702","year":2019},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.184918Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:3d83f2894ed2b8a335c0f2ed2847b8895520d1bd226b17e2610afe8178d40a4d","observation_id":"b155bd7d-e668-438b-931b-e19ca19955c5","resolution":{"observed_at":"2026-08-14T13:14:14.446775Z","resolver_source":"raw_fallback","status":"unresolved"},"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":{"arxiv_id":"1805.08380","last_updated":"2020-04-16T04:57:07Z","snapshot_observed_at":"2026-08-14T19:12:42.000434Z","submitted_at":"2018-05-22T03:58:18Z","title":"Optimal transport natural gradient for statistical manifolds with continuous sample space","version":4},"cited_work":{"arxiv_id":"1805.08380","doi":null,"metadata_source":"pith","pith_arxiv_id":"1805.08380","snapshot_observed_at":"2026-08-14T13:14:14.242982Z","title":"Optimal transport natural gradient for statistical manifolds with continuous sample space","venue":"math.OC","work_id":"88268d42-6862-4662-89c1-8719bff13b54","year":2018},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.189242Z"},"links":{"cited_paper":"/paper/1805.08380","citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:73399e2284c9d427bb9675b934930ec1a67f111bf6c384e036f4664e2e3b3326","observation_id":"c569c55e-b2d4-40d9-8109-80f64d37800d","resolution":{"observed_at":"2026-08-14T13:14:14.250443Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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":"2026-08-14T13:14:14.426768Z","title":"In: Proceedings of the 26th International Conference on World Wide Web, pp","venue":null,"work_id":"5e47e32d-fb94-4c64-90a8-89d6d40ea5a0","year":2017},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.194236Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:3d30e370b9202102d4f30419a639c1939048343ee5f2d400bceb5b64f087bf81","observation_id":"289e9653-ff7f-4e88-ac05-268c8126f87a","resolution":{"observed_at":"2026-08-14T13:14:14.431430Z","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":"2026-08-14T13:14:14.410662Z","title":"In: Proceedings of the 26th International Conference on World Wide Web, pp","venue":null,"work_id":"0197f6a0-b352-4a67-a84f-ec9c950d613a","year":2017},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.199076Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:5b775308371e1e9c5715a0ecd1131b8206b0ba429ae325a23b293155e53e4852","observation_id":"02140f93-c5fd-4aff-9a70-ec4e97826703","resolution":{"observed_at":"2026-08-14T13:14:14.415677Z","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":"2026-08-14T13:14:14.395169Z","title":"In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, vol","venue":null,"work_id":"b40e02f9-1dc1-4183-a6fb-6173760a524e","year":2017},"citing_paper":{"arxiv_id":"1908.05783","last_updated":"2021-11-12T14:36:20Z","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T13:14:14.203844Z"},"links":{"citing_paper":"/paper/1908.05783"},"observation_digest":"sha256:8855f42ae1d61b91c40fb455be1f72b33dc5cac374a02bd9845e135c2ef7c377","observation_id":"c0eefc0b-b589-4ea7-9c1a-e47f7a4df498","resolution":{"observed_at":"2026-08-14T13:14:14.400236Z","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":"1908.05783","last_updated":"2021-11-12T14:36:20Z","latest_version":3,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-17T01:13:27.614507Z","submitted_at":"2019-08-15T22:27:29Z","title":"Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization"},"reference_resolution":{"displayed":49,"state_counts":{"malformed_identifier":0,"metadata_mismatch":4,"parse_uncertain":0,"unresolved":16,"verified_exact":0,"verified_fuzzy":29},"total_outbound_references":49},"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 17 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:1908.05783."}