{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:N6J2QMOJJZPVT6BFBVRVJR23TN","short_pith_number":"pith:N6J2QMOJ","canonical_record":{"source":{"id":"1912.02757","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-05T17:48:18Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f6d0646135a13d9c1469fb94da047c9666b204b37d9db9c6256c4a3df5cb63c5","abstract_canon_sha256":"bc362d20d2cf1eced7dcd15d489c8c430674700ddaad7ba519626890751d1732"},"schema_version":"1.0"},"canonical_sha256":"6f93a831c94e5f59f8250d6354c75b9b50a36a957b0e27c1887bfb73f71f6083","source":{"kind":"arxiv","id":"1912.02757","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.02757","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"arxiv_version","alias_value":"1912.02757v2","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.02757","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"pith_short_12","alias_value":"N6J2QMOJJZPV","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"pith_short_16","alias_value":"N6J2QMOJJZPVT6BF","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"pith_short_8","alias_value":"N6J2QMOJ","created_at":"2026-07-05T01:13:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:N6J2QMOJJZPVT6BFBVRVJR23TN","target":"record","payload":{"canonical_record":{"source":{"id":"1912.02757","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-05T17:48:18Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f6d0646135a13d9c1469fb94da047c9666b204b37d9db9c6256c4a3df5cb63c5","abstract_canon_sha256":"bc362d20d2cf1eced7dcd15d489c8c430674700ddaad7ba519626890751d1732"},"schema_version":"1.0"},"canonical_sha256":"6f93a831c94e5f59f8250d6354c75b9b50a36a957b0e27c1887bfb73f71f6083","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:13:24.164288Z","signature_b64":"BNSDUB3IlRzeD6uPzgThx5UUL/dYjBoy2pc3jrnpwjwawGKfMQkc5cdyEpkkMJvE7P5zoBLu2ve+fAv2jTxjDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6f93a831c94e5f59f8250d6354c75b9b50a36a957b0e27c1887bfb73f71f6083","last_reissued_at":"2026-07-05T01:13:24.163743Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:13:24.163743Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.02757","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":"2026-07-05T01:13:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YH8YhTtguTmBlnUsPAlZjuErjISHpaiOqX6vR8IwCeO33dwyDKGmx+hN99U4J9Q63oYfwY3vGkXVU8GhQS4QBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T03:51:22.812628Z"},"content_sha256":"efb71d0e4486e1e4af4fc0a62a299a941b5789097aaa42bfd47b66365e7cc70a","schema_version":"1.0","event_id":"sha256:efb71d0e4486e1e4af4fc0a62a299a941b5789097aaa42bfd47b66365e7cc70a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:N6J2QMOJJZPVT6BFBVRVJR23TN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Ensembles: A Loss Landscape Perspective","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Balaji Lakshminarayanan, Huiyi Hu, Stanislav Fort","submitted_at":"2019-12-05T17:48:18Z","abstract_excerpt":"Deep ensembles have been empirically shown to be a promising approach for improving accuracy, uncertainty and out-of-distribution robustness of deep learning models. While deep ensembles were theoretically motivated by the bootstrap, non-bootstrap ensembles trained with just random initialization also perform well in practice, which suggests that there could be other explanations for why deep ensembles work well. Bayesian neural networks, which learn distributions over the parameters of the network, are theoretically well-motivated by Bayesian principles, but do not perform as well as deep ens"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.02757","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/1912.02757/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":"2026-07-05T01:13:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Kk13m/S/lw1w5OkA1sDEU2wxytfz6gPxUf1NWYbkuwlLrV/mgHcSSm88nbmjooqQ84zTCQvM1bfYcCkcKtn3Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T03:51:22.813272Z"},"content_sha256":"18a1adefd392b96e7be6dcdd255dd0bffbe71a2dbe7dd7a0f23e01c4ece1fe53","schema_version":"1.0","event_id":"sha256:18a1adefd392b96e7be6dcdd255dd0bffbe71a2dbe7dd7a0f23e01c4ece1fe53"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N6J2QMOJJZPVT6BFBVRVJR23TN/bundle.json","state_url":"https://pith.science/pith/N6J2QMOJJZPVT6BFBVRVJR23TN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N6J2QMOJJZPVT6BFBVRVJR23TN/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":"2026-07-12T03:51:22Z","links":{"resolver":"https://pith.science/pith/N6J2QMOJJZPVT6BFBVRVJR23TN","bundle":"https://pith.science/pith/N6J2QMOJJZPVT6BFBVRVJR23TN/bundle.json","state":"https://pith.science/pith/N6J2QMOJJZPVT6BFBVRVJR23TN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N6J2QMOJJZPVT6BFBVRVJR23TN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:N6J2QMOJJZPVT6BFBVRVJR23TN","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":"bc362d20d2cf1eced7dcd15d489c8c430674700ddaad7ba519626890751d1732","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-05T17:48:18Z","title_canon_sha256":"f6d0646135a13d9c1469fb94da047c9666b204b37d9db9c6256c4a3df5cb63c5"},"schema_version":"1.0","source":{"id":"1912.02757","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.02757","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"arxiv_version","alias_value":"1912.02757v2","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.02757","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"pith_short_12","alias_value":"N6J2QMOJJZPV","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"pith_short_16","alias_value":"N6J2QMOJJZPVT6BF","created_at":"2026-07-05T01:13:24Z"},{"alias_kind":"pith_short_8","alias_value":"N6J2QMOJ","created_at":"2026-07-05T01:13:24Z"}],"graph_snapshots":[{"event_id":"sha256:18a1adefd392b96e7be6dcdd255dd0bffbe71a2dbe7dd7a0f23e01c4ece1fe53","target":"graph","created_at":"2026-07-05T01:13:24Z","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/1912.02757/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep ensembles have been empirically shown to be a promising approach for improving accuracy, uncertainty and out-of-distribution robustness of deep learning models. While deep ensembles were theoretically motivated by the bootstrap, non-bootstrap ensembles trained with just random initialization also perform well in practice, which suggests that there could be other explanations for why deep ensembles work well. Bayesian neural networks, which learn distributions over the parameters of the network, are theoretically well-motivated by Bayesian principles, but do not perform as well as deep ens","authors_text":"Balaji Lakshminarayanan, Huiyi Hu, Stanislav Fort","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.02757","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:efb71d0e4486e1e4af4fc0a62a299a941b5789097aaa42bfd47b66365e7cc70a","target":"record","created_at":"2026-07-05T01:13:24Z","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":"bc362d20d2cf1eced7dcd15d489c8c430674700ddaad7ba519626890751d1732","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-05T17:48:18Z","title_canon_sha256":"f6d0646135a13d9c1469fb94da047c9666b204b37d9db9c6256c4a3df5cb63c5"},"schema_version":"1.0","source":{"id":"1912.02757","kind":"arxiv","version":2}},"canonical_sha256":"6f93a831c94e5f59f8250d6354c75b9b50a36a957b0e27c1887bfb73f71f6083","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6f93a831c94e5f59f8250d6354c75b9b50a36a957b0e27c1887bfb73f71f6083","first_computed_at":"2026-07-05T01:13:24.163743Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:13:24.163743Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BNSDUB3IlRzeD6uPzgThx5UUL/dYjBoy2pc3jrnpwjwawGKfMQkc5cdyEpkkMJvE7P5zoBLu2ve+fAv2jTxjDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:13:24.164288Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.02757","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:efb71d0e4486e1e4af4fc0a62a299a941b5789097aaa42bfd47b66365e7cc70a","sha256:18a1adefd392b96e7be6dcdd255dd0bffbe71a2dbe7dd7a0f23e01c4ece1fe53"],"state_sha256":"b73732163e630c559dcf40ab50cc497c0882f63281fb1d2d9cce937fbe8a499d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ElY9Aipqks57Y4GU/4z0VCJSWL4L8DE0KgWR1FoudeXBPW2sxRNk6ldIIOicVrPWnebkmshaYg924BNgyDWKBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T03:51:22.816337Z","bundle_sha256":"3c61221983fb4b387ab538c66127bc5c9e51fe060343caabfc7bb8d24e1fba39"}}