{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:2ZIVBJS46BIDB7A522353VZJE7","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":"af7825ce75d97b6823f20bf878078823230df7c569401229fd90a129f890245a","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-02-18T10:22:13Z","title_canon_sha256":"e0f5f4f1469194aca53bb55e1abc6fe66d253cd8e034dde87d0de7ea8595b5c0"},"schema_version":"1.0","source":{"id":"1902.06494","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.06494","created_at":"2026-05-17T23:53:45Z"},{"alias_kind":"arxiv_version","alias_value":"1902.06494v1","created_at":"2026-05-17T23:53:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.06494","created_at":"2026-05-17T23:53:45Z"},{"alias_kind":"pith_short_12","alias_value":"2ZIVBJS46BID","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"2ZIVBJS46BIDB7A5","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"2ZIVBJS4","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:0fb6859ce0f154a05808dccd77d3e6a385ab82a07121c35bf1474e15d0da16a5","target":"graph","created_at":"2026-05-17T23:53:45Z","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"},"paper":{"abstract_excerpt":"Some machine learning applications require continual learning - where data comes in a sequence of datasets, each is used for training and then permanently discarded. From a Bayesian perspective, continual learning seems straightforward: Given the model posterior one would simply use this as the prior for the next task. However, exact posterior evaluation is intractable with many models, especially with Bayesian neural networks (BNNs). Instead, posterior approximations are often sought. Unfortunately, when posterior approximations are used, prior-focused approaches do not succeed in evaluations","authors_text":"Sebastian Farquhar, Yarin Gal","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-02-18T10:22:13Z","title":"A Unifying Bayesian View of Continual Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.06494","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":"sha256:0f36d12320fb6283f19b329b22e0930ed32f794ae8a53c38daecd7e8421e04d4","target":"record","created_at":"2026-05-17T23:53:45Z","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":"af7825ce75d97b6823f20bf878078823230df7c569401229fd90a129f890245a","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-02-18T10:22:13Z","title_canon_sha256":"e0f5f4f1469194aca53bb55e1abc6fe66d253cd8e034dde87d0de7ea8595b5c0"},"schema_version":"1.0","source":{"id":"1902.06494","kind":"arxiv","version":1}},"canonical_sha256":"d65150a65cf05030fc1dd6b7ddd72927d1b832db8f917086f99763acfc81a584","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d65150a65cf05030fc1dd6b7ddd72927d1b832db8f917086f99763acfc81a584","first_computed_at":"2026-05-17T23:53:45.300559Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:53:45.300559Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ylOfowa6lKCtSENwc+nPYbmpLuDNADgrKBRsc5ETuZq89VcPk4wm4tEDLR916XVQcMFjoaOoHCF9xBVP9gwBAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:53:45.301092Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.06494","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0f36d12320fb6283f19b329b22e0930ed32f794ae8a53c38daecd7e8421e04d4","sha256:0fb6859ce0f154a05808dccd77d3e6a385ab82a07121c35bf1474e15d0da16a5"],"state_sha256":"0704a2b7f138557523fc46dbfe9ef4e63dfeeaefe934c251631d8a8832d65b35"}