{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:TAZDZEABI44KMS3SKUNYT76OQM","short_pith_number":"pith:TAZDZEAB","canonical_record":{"source":{"id":"2203.04413","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T21:34:46Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"0dbc21c8639b0e9883a421444470ee3118a14ac8e848f63cd54180c8200e55e1","abstract_canon_sha256":"519067d9b62edc29fa6536b2562b04fbc11f16cf3ae2dee2f0960496f83b0ef2"},"schema_version":"1.0"},"canonical_sha256":"98323c90014738a64b72551b89ffce83030b17b3e416aa728a6721289f57f720","source":{"kind":"arxiv","id":"2203.04413","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04413","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04413v1","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04413","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"pith_short_12","alias_value":"TAZDZEABI44K","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"pith_short_16","alias_value":"TAZDZEABI44KMS3S","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"pith_short_8","alias_value":"TAZDZEAB","created_at":"2026-07-05T04:13:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:TAZDZEABI44KMS3SKUNYT76OQM","target":"record","payload":{"canonical_record":{"source":{"id":"2203.04413","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T21:34:46Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"0dbc21c8639b0e9883a421444470ee3118a14ac8e848f63cd54180c8200e55e1","abstract_canon_sha256":"519067d9b62edc29fa6536b2562b04fbc11f16cf3ae2dee2f0960496f83b0ef2"},"schema_version":"1.0"},"canonical_sha256":"98323c90014738a64b72551b89ffce83030b17b3e416aa728a6721289f57f720","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:13:12.866968Z","signature_b64":"tTrdyBl1WdgQTjxquba3lzGMBG7Tla4Tuty1tW9i3TBy87PSPz0Ug0hJI9dnIuCFgS2Bi17AznYTJKpncgD1Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"98323c90014738a64b72551b89ffce83030b17b3e416aa728a6721289f57f720","last_reissued_at":"2026-07-05T04:13:12.866513Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:13:12.866513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.04413","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":"2026-07-05T04:13:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a9UNHO0KSbDt07vIBbTcJWcgkV09QdPW2poncPAU+jUZsmOzKS97QtnBJfevL6+3lxacdYm1M+JwYawvPXeYBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:04:48.209160Z"},"content_sha256":"29019ed77124409984dbc205b3252d455ff60676e6da8c0c94a7cfbc783808af","schema_version":"1.0","event_id":"sha256:29019ed77124409984dbc205b3252d455ff60676e6da8c0c94a7cfbc783808af"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:TAZDZEABI44KMS3SKUNYT76OQM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Score matching enables causal discovery of nonlinear additive noise models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Bernhard Sch\\\"olkopf, Chris Russel, Dominik Janzing, Francesco Locatello, Matth\\\"aus Kleindessner, Paul Rolland, Volkan Cevher","submitted_at":"2022-03-08T21:34:46Z","abstract_excerpt":"This paper demonstrates how to recover causal graphs from the score of the data distribution in non-linear additive (Gaussian) noise models. Using score matching algorithms as a building block, we show how to design a new generation of scalable causal discovery methods. To showcase our approach, we also propose a new efficient method for approximating the score's Jacobian, enabling to recover the causal graph. Empirically, we find that the new algorithm, called SCORE, is competitive with state-of-the-art causal discovery methods while being significantly faster."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04413","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/2203.04413/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":"2026-07-05T04:13:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3uKpJaFYORKPe+pNJqpCaoVBxq47SbOb7adU143kzcpgAKkRdu3iq/GYhDBtQQYFr7VgFI6XwhEHIS5G2ikuDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:04:48.209672Z"},"content_sha256":"237020cff38cef3ce26927a6ed3614330361adff03921df039b309b11c9e5e8d","schema_version":"1.0","event_id":"sha256:237020cff38cef3ce26927a6ed3614330361adff03921df039b309b11c9e5e8d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TAZDZEABI44KMS3SKUNYT76OQM/bundle.json","state_url":"https://pith.science/pith/TAZDZEABI44KMS3SKUNYT76OQM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TAZDZEABI44KMS3SKUNYT76OQM/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":"2026-08-06T13:04:48Z","links":{"resolver":"https://pith.science/pith/TAZDZEABI44KMS3SKUNYT76OQM","bundle":"https://pith.science/pith/TAZDZEABI44KMS3SKUNYT76OQM/bundle.json","state":"https://pith.science/pith/TAZDZEABI44KMS3SKUNYT76OQM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TAZDZEABI44KMS3SKUNYT76OQM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:TAZDZEABI44KMS3SKUNYT76OQM","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":"519067d9b62edc29fa6536b2562b04fbc11f16cf3ae2dee2f0960496f83b0ef2","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T21:34:46Z","title_canon_sha256":"0dbc21c8639b0e9883a421444470ee3118a14ac8e848f63cd54180c8200e55e1"},"schema_version":"1.0","source":{"id":"2203.04413","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04413","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04413v1","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04413","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"pith_short_12","alias_value":"TAZDZEABI44K","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"pith_short_16","alias_value":"TAZDZEABI44KMS3S","created_at":"2026-07-05T04:13:12Z"},{"alias_kind":"pith_short_8","alias_value":"TAZDZEAB","created_at":"2026-07-05T04:13:12Z"}],"graph_snapshots":[{"event_id":"sha256:237020cff38cef3ce26927a6ed3614330361adff03921df039b309b11c9e5e8d","target":"graph","created_at":"2026-07-05T04:13:12Z","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/2203.04413/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper demonstrates how to recover causal graphs from the score of the data distribution in non-linear additive (Gaussian) noise models. Using score matching algorithms as a building block, we show how to design a new generation of scalable causal discovery methods. To showcase our approach, we also propose a new efficient method for approximating the score's Jacobian, enabling to recover the causal graph. Empirically, we find that the new algorithm, called SCORE, is competitive with state-of-the-art causal discovery methods while being significantly faster.","authors_text":"Bernhard Sch\\\"olkopf, Chris Russel, Dominik Janzing, Francesco Locatello, Matth\\\"aus Kleindessner, Paul Rolland, Volkan Cevher","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T21:34:46Z","title":"Score matching enables causal discovery of nonlinear additive noise models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04413","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":"sha256:29019ed77124409984dbc205b3252d455ff60676e6da8c0c94a7cfbc783808af","target":"record","created_at":"2026-07-05T04:13:12Z","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":"519067d9b62edc29fa6536b2562b04fbc11f16cf3ae2dee2f0960496f83b0ef2","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-08T21:34:46Z","title_canon_sha256":"0dbc21c8639b0e9883a421444470ee3118a14ac8e848f63cd54180c8200e55e1"},"schema_version":"1.0","source":{"id":"2203.04413","kind":"arxiv","version":1}},"canonical_sha256":"98323c90014738a64b72551b89ffce83030b17b3e416aa728a6721289f57f720","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"98323c90014738a64b72551b89ffce83030b17b3e416aa728a6721289f57f720","first_computed_at":"2026-07-05T04:13:12.866513Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:13:12.866513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tTrdyBl1WdgQTjxquba3lzGMBG7Tla4Tuty1tW9i3TBy87PSPz0Ug0hJI9dnIuCFgS2Bi17AznYTJKpncgD1Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T04:13:12.866968Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.04413","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:29019ed77124409984dbc205b3252d455ff60676e6da8c0c94a7cfbc783808af","sha256:237020cff38cef3ce26927a6ed3614330361adff03921df039b309b11c9e5e8d"],"state_sha256":"2821ebaaed5044713a6e8f5ea12912d98293e794ba2cb2657d769f8db3064420"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fAJNNp6xsmdL65cI6ScRRQgM46TMWR1w3TqgOTYdwyGsYfLVfC0v320sCM3rhCmHn56yRf+fg6kyWL4WzbGHDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T13:04:48.213283Z","bundle_sha256":"ad133027f40830ec4c611c39b86ad940e0b575ee76128d32d90caa9ed6dbf039"}}