{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:25ZMLWCR5LKOFV5BHIE62P4H4O","short_pith_number":"pith:25ZMLWCR","canonical_record":{"source":{"id":"2106.04914","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-09T08:50:22Z","cross_cats_sorted":[],"title_canon_sha256":"cc05cf1223606702f278c72fa942c9e63287e328dcc6901f8773715861cd8420","abstract_canon_sha256":"c3cff674cde5839c2bc3aedaa919b4ca564b0973ad42031c5023d05be50a9d24"},"schema_version":"1.0"},"canonical_sha256":"d772c5d851ead4e2d7a13a09ed3f87e3b7ec6781e54272ac7905639caced17c3","source":{"kind":"arxiv","id":"2106.04914","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.04914","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"arxiv_version","alias_value":"2106.04914v1","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.04914","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"pith_short_12","alias_value":"25ZMLWCR5LKO","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"pith_short_16","alias_value":"25ZMLWCR5LKOFV5B","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"pith_short_8","alias_value":"25ZMLWCR","created_at":"2026-07-05T02:47:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:25ZMLWCR5LKOFV5BHIE62P4H4O","target":"record","payload":{"canonical_record":{"source":{"id":"2106.04914","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-09T08:50:22Z","cross_cats_sorted":[],"title_canon_sha256":"cc05cf1223606702f278c72fa942c9e63287e328dcc6901f8773715861cd8420","abstract_canon_sha256":"c3cff674cde5839c2bc3aedaa919b4ca564b0973ad42031c5023d05be50a9d24"},"schema_version":"1.0"},"canonical_sha256":"d772c5d851ead4e2d7a13a09ed3f87e3b7ec6781e54272ac7905639caced17c3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:47:50.640259Z","signature_b64":"n7JnYGMFJpkkALRQQl6+wCXLspWj/gR0WHhL/23tnandwT5mCtocKvujWo1uQG4Rz5240F6RVObIs3KwnxhuAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d772c5d851ead4e2d7a13a09ed3f87e3b7ec6781e54272ac7905639caced17c3","last_reissued_at":"2026-07-05T02:47:50.639843Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:47:50.639843Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.04914","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:47:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D1A3znNNlXkSVklUR8M1xq1g56T+6vE/Ay11CuLvz2CQlbl6kZgadvL6x3tgbQqLdOeGX3uWUdnwpK1dyXTyAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T17:31:24.666699Z"},"content_sha256":"e44c27b2038c6c22adab6e84ef647452031ca8ba0827c0a791ba2b6eb193d31a","schema_version":"1.0","event_id":"sha256:e44c27b2038c6c22adab6e84ef647452031ca8ba0827c0a791ba2b6eb193d31a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:25ZMLWCR5LKOFV5BHIE62P4H4O","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploiting Learned Symmetries in Group Equivariant Convolutions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Attila Lengyel, Jan C. van Gemert","submitted_at":"2021-06-09T08:50:22Z","abstract_excerpt":"Group Equivariant Convolutions (GConvs) enable convolutional neural networks to be equivariant to various transformation groups, but at an additional parameter and compute cost. We investigate the filter parameters learned by GConvs and find certain conditions under which they become highly redundant. We show that GConvs can be efficiently decomposed into depthwise separable convolutions while preserving equivariance properties and demonstrate improved performance and data efficiency on two datasets. All code is publicly available at github.com/Attila94/SepGrouPy."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.04914","kind":"arxiv","version":1},"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/2106.04914/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":"2026-07-05T02:47:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CPuVWQYsfKodJHdF4NA7Hp+kir2s3hG54eQ7OfLL34ChTBvPSUIgGcguUVmtPtIonrqM9YAO3TgdmEEEd4QeDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T17:31:24.667202Z"},"content_sha256":"0bf017755dd099dd890e12d155d1cb9fe97260314653e5287d24702020f9d411","schema_version":"1.0","event_id":"sha256:0bf017755dd099dd890e12d155d1cb9fe97260314653e5287d24702020f9d411"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/25ZMLWCR5LKOFV5BHIE62P4H4O/bundle.json","state_url":"https://pith.science/pith/25ZMLWCR5LKOFV5BHIE62P4H4O/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/25ZMLWCR5LKOFV5BHIE62P4H4O/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":"2026-08-04T17:31:24Z","links":{"resolver":"https://pith.science/pith/25ZMLWCR5LKOFV5BHIE62P4H4O","bundle":"https://pith.science/pith/25ZMLWCR5LKOFV5BHIE62P4H4O/bundle.json","state":"https://pith.science/pith/25ZMLWCR5LKOFV5BHIE62P4H4O/state.json","well_known_bundle":"https://pith.science/.well-known/pith/25ZMLWCR5LKOFV5BHIE62P4H4O/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:25ZMLWCR5LKOFV5BHIE62P4H4O","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":"c3cff674cde5839c2bc3aedaa919b4ca564b0973ad42031c5023d05be50a9d24","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-09T08:50:22Z","title_canon_sha256":"cc05cf1223606702f278c72fa942c9e63287e328dcc6901f8773715861cd8420"},"schema_version":"1.0","source":{"id":"2106.04914","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.04914","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"arxiv_version","alias_value":"2106.04914v1","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.04914","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"pith_short_12","alias_value":"25ZMLWCR5LKO","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"pith_short_16","alias_value":"25ZMLWCR5LKOFV5B","created_at":"2026-07-05T02:47:50Z"},{"alias_kind":"pith_short_8","alias_value":"25ZMLWCR","created_at":"2026-07-05T02:47:50Z"}],"graph_snapshots":[{"event_id":"sha256:0bf017755dd099dd890e12d155d1cb9fe97260314653e5287d24702020f9d411","target":"graph","created_at":"2026-07-05T02:47:50Z","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/2106.04914/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Group Equivariant Convolutions (GConvs) enable convolutional neural networks to be equivariant to various transformation groups, but at an additional parameter and compute cost. We investigate the filter parameters learned by GConvs and find certain conditions under which they become highly redundant. We show that GConvs can be efficiently decomposed into depthwise separable convolutions while preserving equivariance properties and demonstrate improved performance and data efficiency on two datasets. All code is publicly available at github.com/Attila94/SepGrouPy.","authors_text":"Attila Lengyel, Jan C. van Gemert","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-09T08:50:22Z","title":"Exploiting Learned Symmetries in Group Equivariant Convolutions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.04914","kind":"arxiv","version":1},"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:e44c27b2038c6c22adab6e84ef647452031ca8ba0827c0a791ba2b6eb193d31a","target":"record","created_at":"2026-07-05T02:47:50Z","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":"c3cff674cde5839c2bc3aedaa919b4ca564b0973ad42031c5023d05be50a9d24","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-09T08:50:22Z","title_canon_sha256":"cc05cf1223606702f278c72fa942c9e63287e328dcc6901f8773715861cd8420"},"schema_version":"1.0","source":{"id":"2106.04914","kind":"arxiv","version":1}},"canonical_sha256":"d772c5d851ead4e2d7a13a09ed3f87e3b7ec6781e54272ac7905639caced17c3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d772c5d851ead4e2d7a13a09ed3f87e3b7ec6781e54272ac7905639caced17c3","first_computed_at":"2026-07-05T02:47:50.639843Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:47:50.639843Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"n7JnYGMFJpkkALRQQl6+wCXLspWj/gR0WHhL/23tnandwT5mCtocKvujWo1uQG4Rz5240F6RVObIs3KwnxhuAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:47:50.640259Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.04914","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e44c27b2038c6c22adab6e84ef647452031ca8ba0827c0a791ba2b6eb193d31a","sha256:0bf017755dd099dd890e12d155d1cb9fe97260314653e5287d24702020f9d411"],"state_sha256":"31d0b86cb77c2aa322049e47768be0d43832e946b407248d87c4ccb7e46849c7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w9Mf9IB0mrIlL4onjK1Dc0ptUnt8EIABPJ7tAcTVlKuAqM4BhMZrwkjIqyC3EAlxMB3mwn57jUcOygmboFfcDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T17:31:24.671926Z","bundle_sha256":"90208e4acc4b120b7e130399c2d87ab7fa59c2ce719d685839766527bcd1f501"}}