{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:H2IOW2ADBRLOHORBEUVBI5656B","short_pith_number":"pith:H2IOW2AD","canonical_record":{"source":{"id":"2110.10211","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-19T19:17:32Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"92e610fa96703150f2fe1882b7b77db5cbbb3777b768d1d566ff1c9c8783a6b6","abstract_canon_sha256":"de1e57f128ef7fd5379bf20ac7f9b21d340e6cc5b97bef0b430661f8de8f18be"},"schema_version":"1.0"},"canonical_sha256":"3e90eb68030c56e3ba21252a1477ddf05c6e58024c47af7c08367cef0a5912e5","source":{"kind":"arxiv","id":"2110.10211","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.10211","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"arxiv_version","alias_value":"2110.10211v3","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.10211","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"pith_short_12","alias_value":"H2IOW2ADBRLO","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"pith_short_16","alias_value":"H2IOW2ADBRLOHORB","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"pith_short_8","alias_value":"H2IOW2AD","created_at":"2026-07-05T05:33:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:H2IOW2ADBRLOHORBEUVBI5656B","target":"record","payload":{"canonical_record":{"source":{"id":"2110.10211","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-19T19:17:32Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"92e610fa96703150f2fe1882b7b77db5cbbb3777b768d1d566ff1c9c8783a6b6","abstract_canon_sha256":"de1e57f128ef7fd5379bf20ac7f9b21d340e6cc5b97bef0b430661f8de8f18be"},"schema_version":"1.0"},"canonical_sha256":"3e90eb68030c56e3ba21252a1477ddf05c6e58024c47af7c08367cef0a5912e5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:33:06.712073Z","signature_b64":"12M7FsUkq6xpk8s/54LZQ0YC1UBQAXBM6M5CRQtUxlm8b1Tn6qfxl8Efn/WtJz32LdDuDXlJ7vkB5A2eMQnDAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e90eb68030c56e3ba21252a1477ddf05c6e58024c47af7c08367cef0a5912e5","last_reissued_at":"2026-07-05T05:33:06.711573Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:33:06.711573Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.10211","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:33:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Jw6Agz9HAqafuQSPsXD7lZ/q8AClWsQCeUQ+31B1548y1IenoeU81x7tcGRdt435PN6t/MMSzFoQW38Ge78vCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T11:45:01.592470Z"},"content_sha256":"5ec37dd644d84d9f21075813eae19d5ebf399e98b941359731c71806112d4155","schema_version":"1.0","event_id":"sha256:5ec37dd644d84d9f21075813eae19d5ebf399e98b941359731c71806112d4155"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:H2IOW2ADBRLOHORBEUVBI5656B","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Partial Equivariances from Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"David W. Romero, Suhas Lohit","submitted_at":"2021-10-19T19:17:32Z","abstract_excerpt":"Group Convolutional Neural Networks (G-CNNs) constrain learned features to respect the symmetries in the selected group, and lead to better generalization when these symmetries appear in the data. If this is not the case, however, equivariance leads to overly constrained models and worse performance. Frequently, transformations occurring in data can be better represented by a subset of a group than by a group as a whole, e.g., rotations in $[-90^{\\circ}, 90^{\\circ}]$. In such cases, a model that respects equivariance $\\textit{partially}$ is better suited to represent the data. In addition, rel"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.10211","kind":"arxiv","version":3},"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/2110.10211/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":"2026-07-05T05:33:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wcC/Zw5iBSq2UQPpo9Z1G+4lvpKVtYGUKVn77UtXoUfYvmEiTy7fHQYXb+gZTyo/AqLCXjrkEG5f3UFAAHJTAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T11:45:01.592844Z"},"content_sha256":"844239779e3ae5629dd3f8aae033b7c54bbedf9618bd4e97bfcd3206eaf42d4c","schema_version":"1.0","event_id":"sha256:844239779e3ae5629dd3f8aae033b7c54bbedf9618bd4e97bfcd3206eaf42d4c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H2IOW2ADBRLOHORBEUVBI5656B/bundle.json","state_url":"https://pith.science/pith/H2IOW2ADBRLOHORBEUVBI5656B/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H2IOW2ADBRLOHORBEUVBI5656B/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":"2026-07-05T11:45:01Z","links":{"resolver":"https://pith.science/pith/H2IOW2ADBRLOHORBEUVBI5656B","bundle":"https://pith.science/pith/H2IOW2ADBRLOHORBEUVBI5656B/bundle.json","state":"https://pith.science/pith/H2IOW2ADBRLOHORBEUVBI5656B/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H2IOW2ADBRLOHORBEUVBI5656B/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:H2IOW2ADBRLOHORBEUVBI5656B","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":"de1e57f128ef7fd5379bf20ac7f9b21d340e6cc5b97bef0b430661f8de8f18be","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-19T19:17:32Z","title_canon_sha256":"92e610fa96703150f2fe1882b7b77db5cbbb3777b768d1d566ff1c9c8783a6b6"},"schema_version":"1.0","source":{"id":"2110.10211","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.10211","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"arxiv_version","alias_value":"2110.10211v3","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.10211","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"pith_short_12","alias_value":"H2IOW2ADBRLO","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"pith_short_16","alias_value":"H2IOW2ADBRLOHORB","created_at":"2026-07-05T05:33:06Z"},{"alias_kind":"pith_short_8","alias_value":"H2IOW2AD","created_at":"2026-07-05T05:33:06Z"}],"graph_snapshots":[{"event_id":"sha256:844239779e3ae5629dd3f8aae033b7c54bbedf9618bd4e97bfcd3206eaf42d4c","target":"graph","created_at":"2026-07-05T05:33:06Z","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/2110.10211/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Group Convolutional Neural Networks (G-CNNs) constrain learned features to respect the symmetries in the selected group, and lead to better generalization when these symmetries appear in the data. If this is not the case, however, equivariance leads to overly constrained models and worse performance. Frequently, transformations occurring in data can be better represented by a subset of a group than by a group as a whole, e.g., rotations in $[-90^{\\circ}, 90^{\\circ}]$. In such cases, a model that respects equivariance $\\textit{partially}$ is better suited to represent the data. In addition, rel","authors_text":"David W. Romero, Suhas Lohit","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-19T19:17:32Z","title":"Learning Partial Equivariances from Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.10211","kind":"arxiv","version":3},"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":"sha256:5ec37dd644d84d9f21075813eae19d5ebf399e98b941359731c71806112d4155","target":"record","created_at":"2026-07-05T05:33:06Z","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":"de1e57f128ef7fd5379bf20ac7f9b21d340e6cc5b97bef0b430661f8de8f18be","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-19T19:17:32Z","title_canon_sha256":"92e610fa96703150f2fe1882b7b77db5cbbb3777b768d1d566ff1c9c8783a6b6"},"schema_version":"1.0","source":{"id":"2110.10211","kind":"arxiv","version":3}},"canonical_sha256":"3e90eb68030c56e3ba21252a1477ddf05c6e58024c47af7c08367cef0a5912e5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e90eb68030c56e3ba21252a1477ddf05c6e58024c47af7c08367cef0a5912e5","first_computed_at":"2026-07-05T05:33:06.711573Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:33:06.711573Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"12M7FsUkq6xpk8s/54LZQ0YC1UBQAXBM6M5CRQtUxlm8b1Tn6qfxl8Efn/WtJz32LdDuDXlJ7vkB5A2eMQnDAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:33:06.712073Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.10211","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5ec37dd644d84d9f21075813eae19d5ebf399e98b941359731c71806112d4155","sha256:844239779e3ae5629dd3f8aae033b7c54bbedf9618bd4e97bfcd3206eaf42d4c"],"state_sha256":"cf64533f62d4b652cd7a3cddc7a3f341f2d211612e753adb4dffeccfce1e9179"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wKtZPyMyFgkpgQfWWwGhI9Hkbiu0mTlMOB9PTMmscVh9qHMFrOPdQHcYFKNKRmMTpoED5/CAyBcFGSWeRGDuCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T11:45:01.594768Z","bundle_sha256":"cce85e020123c9efc963f0253196b08e82ce505a45dc7dbd0749154a2fa7b18c"}}