{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:B7GKG25HJP3HRXPBWTWZVB3EA2","short_pith_number":"pith:B7GKG25H","canonical_record":{"source":{"id":"2110.15037","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T11:51:08Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"d73da29a62f62c2e6efde5fb18aeeda512f370755550aae13628bc23ab4d2fb2","abstract_canon_sha256":"cd8bde335485e9f4cd6708defbaf15b625d366886a67cff07dabf3ec99dbb394"},"schema_version":"1.0"},"canonical_sha256":"0fcca36ba74bf678dde1b4ed9a87640680327e092552cd296063207b9a1c98db","source":{"kind":"arxiv","id":"2110.15037","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.15037","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"arxiv_version","alias_value":"2110.15037v2","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.15037","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"pith_short_12","alias_value":"B7GKG25HJP3H","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"pith_short_16","alias_value":"B7GKG25HJP3HRXPB","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"pith_short_8","alias_value":"B7GKG25H","created_at":"2026-07-05T04:25:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:B7GKG25HJP3HRXPBWTWZVB3EA2","target":"record","payload":{"canonical_record":{"source":{"id":"2110.15037","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T11:51:08Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"d73da29a62f62c2e6efde5fb18aeeda512f370755550aae13628bc23ab4d2fb2","abstract_canon_sha256":"cd8bde335485e9f4cd6708defbaf15b625d366886a67cff07dabf3ec99dbb394"},"schema_version":"1.0"},"canonical_sha256":"0fcca36ba74bf678dde1b4ed9a87640680327e092552cd296063207b9a1c98db","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:25:47.928342Z","signature_b64":"ADnmVDXnZ1LftYJ/E9ecSe3RRhSMACAEhKEAUGGazSqymGaUKvWj+QAVRocYUVetrabEPJDWxoSaJDkSSiamBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0fcca36ba74bf678dde1b4ed9a87640680327e092552cd296063207b9a1c98db","last_reissued_at":"2026-07-05T04:25:47.927768Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:25:47.927768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.15037","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:25:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CX8gUc++sU21KM6Gn2zzOjguXtrDDo7MLiyfUCFFDpfvc8cxYqjs9ukJRHsUdG11c/sG6h6HVT2NrV6lGNzJAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:18:04.907565Z"},"content_sha256":"5d3c097dafbb0136dc842af82568e99f3d503428cf10cdf74fd662b69989b8a1","schema_version":"1.0","event_id":"sha256:5d3c097dafbb0136dc842af82568e99f3d503428cf10cdf74fd662b69989b8a1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:B7GKG25HJP3HRXPBWTWZVB3EA2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Deep Representation with Energy-Based Self-Expressiveness for Subspace Clustering","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Changsheng Li, Guoren Wang, Shiye Wang, Yanming Li, Ye Yuan","submitted_at":"2021-10-28T11:51:08Z","abstract_excerpt":"Deep subspace clustering has attracted increasing attention in recent years. Almost all the existing works are required to load the whole training data into one batch for learning the self-expressive coefficients in the framework of deep learning. Although these methods achieve promising results, such a learning fashion severely prevents from the usage of deeper neural network architectures (e.g., ResNet), leading to the limited representation abilities of the models. In this paper, we propose a new deep subspace clustering framework, motivated by the energy-based models. In contrast to previo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.15037","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2110.15037/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:25:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yzKcxYASoMCBhez4JEuaQXVPDiDafHEIP/7gWmRt5dCxaiJFP58L3qq5hTK7PxvT+a8tZby3fkGzuYoLQuF6AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:18:04.908105Z"},"content_sha256":"9a566133a10af6eb3277a66726bdf236ab8e0464386e1f04093456ddf218600d","schema_version":"1.0","event_id":"sha256:9a566133a10af6eb3277a66726bdf236ab8e0464386e1f04093456ddf218600d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B7GKG25HJP3HRXPBWTWZVB3EA2/bundle.json","state_url":"https://pith.science/pith/B7GKG25HJP3HRXPBWTWZVB3EA2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B7GKG25HJP3HRXPBWTWZVB3EA2/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T08:18:04Z","links":{"resolver":"https://pith.science/pith/B7GKG25HJP3HRXPBWTWZVB3EA2","bundle":"https://pith.science/pith/B7GKG25HJP3HRXPBWTWZVB3EA2/bundle.json","state":"https://pith.science/pith/B7GKG25HJP3HRXPBWTWZVB3EA2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B7GKG25HJP3HRXPBWTWZVB3EA2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:B7GKG25HJP3HRXPBWTWZVB3EA2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"cd8bde335485e9f4cd6708defbaf15b625d366886a67cff07dabf3ec99dbb394","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T11:51:08Z","title_canon_sha256":"d73da29a62f62c2e6efde5fb18aeeda512f370755550aae13628bc23ab4d2fb2"},"schema_version":"1.0","source":{"id":"2110.15037","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.15037","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"arxiv_version","alias_value":"2110.15037v2","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.15037","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"pith_short_12","alias_value":"B7GKG25HJP3H","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"pith_short_16","alias_value":"B7GKG25HJP3HRXPB","created_at":"2026-07-05T04:25:47Z"},{"alias_kind":"pith_short_8","alias_value":"B7GKG25H","created_at":"2026-07-05T04:25:47Z"}],"graph_snapshots":[{"event_id":"sha256:9a566133a10af6eb3277a66726bdf236ab8e0464386e1f04093456ddf218600d","target":"graph","created_at":"2026-07-05T04:25:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2110.15037/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep subspace clustering has attracted increasing attention in recent years. Almost all the existing works are required to load the whole training data into one batch for learning the self-expressive coefficients in the framework of deep learning. Although these methods achieve promising results, such a learning fashion severely prevents from the usage of deeper neural network architectures (e.g., ResNet), leading to the limited representation abilities of the models. In this paper, we propose a new deep subspace clustering framework, motivated by the energy-based models. In contrast to previo","authors_text":"Changsheng Li, Guoren Wang, Shiye Wang, Yanming Li, Ye Yuan","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T11:51:08Z","title":"Learning Deep Representation with Energy-Based Self-Expressiveness for Subspace Clustering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.15037","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:5d3c097dafbb0136dc842af82568e99f3d503428cf10cdf74fd662b69989b8a1","target":"record","created_at":"2026-07-05T04:25:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"cd8bde335485e9f4cd6708defbaf15b625d366886a67cff07dabf3ec99dbb394","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-10-28T11:51:08Z","title_canon_sha256":"d73da29a62f62c2e6efde5fb18aeeda512f370755550aae13628bc23ab4d2fb2"},"schema_version":"1.0","source":{"id":"2110.15037","kind":"arxiv","version":2}},"canonical_sha256":"0fcca36ba74bf678dde1b4ed9a87640680327e092552cd296063207b9a1c98db","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0fcca36ba74bf678dde1b4ed9a87640680327e092552cd296063207b9a1c98db","first_computed_at":"2026-07-05T04:25:47.927768Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:25:47.927768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ADnmVDXnZ1LftYJ/E9ecSe3RRhSMACAEhKEAUGGazSqymGaUKvWj+QAVRocYUVetrabEPJDWxoSaJDkSSiamBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:25:47.928342Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.15037","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5d3c097dafbb0136dc842af82568e99f3d503428cf10cdf74fd662b69989b8a1","sha256:9a566133a10af6eb3277a66726bdf236ab8e0464386e1f04093456ddf218600d"],"state_sha256":"9d42d4ce047befa1a3128ab801484079efa2fe844f57c2f6d90b58a5aed218fd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PCgCrhQLwGmGpLQ5ccWN6nf/SzZzdlgbX0+U+wCDUrTgPKl0+bU7LLs1gDiKCCmlcIjEzCa1B4ug6FkIomv0BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T08:18:04.911969Z","bundle_sha256":"6c4bec51e9080d718318a33b5fe45b989a6aa4dbe09a96fa3fdecafef6e870f0"}}