{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:V5BO3PICUDV5LWCUTXJXFCUAZU","short_pith_number":"pith:V5BO3PIC","canonical_record":{"source":{"id":"2107.05481","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-07-02T22:35:21Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6cb1e14a09b739b25b59c827af1c72719e448216ceb1e87bd973c3707c170c4c","abstract_canon_sha256":"38adccc7c442b971d4d9a003868bbb094021278486eb543f29f67f4461741eb6"},"schema_version":"1.0"},"canonical_sha256":"af42edbd02a0ebd5d8549dd3728a80cd0d07061866c5b97f230fdf399bad8be0","source":{"kind":"arxiv","id":"2107.05481","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.05481","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"arxiv_version","alias_value":"2107.05481v1","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.05481","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"pith_short_12","alias_value":"V5BO3PICUDV5","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"pith_short_16","alias_value":"V5BO3PICUDV5LWCU","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"pith_short_8","alias_value":"V5BO3PIC","created_at":"2026-07-05T02:57:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:V5BO3PICUDV5LWCUTXJXFCUAZU","target":"record","payload":{"canonical_record":{"source":{"id":"2107.05481","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-07-02T22:35:21Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6cb1e14a09b739b25b59c827af1c72719e448216ceb1e87bd973c3707c170c4c","abstract_canon_sha256":"38adccc7c442b971d4d9a003868bbb094021278486eb543f29f67f4461741eb6"},"schema_version":"1.0"},"canonical_sha256":"af42edbd02a0ebd5d8549dd3728a80cd0d07061866c5b97f230fdf399bad8be0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:57:03.261607Z","signature_b64":"nQChnqZFjsQKrqx12nd8H9ltpgzaM9EVOpYxwVg2rMbf4wufK0EkhgfSHO6jI5Y2fu3IUSVUm1caZs4LO2tADQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af42edbd02a0ebd5d8549dd3728a80cd0d07061866c5b97f230fdf399bad8be0","last_reissued_at":"2026-07-05T02:57:03.261270Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:57:03.261270Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2107.05481","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":"2026-07-05T02:57:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sv/DQR9Cuu84TXSscED5pGf1qAr/IuQsKpmk9PbH983bTIku5ammph/aCrK6RybOHKxRvVrrnhhucISWOUxpCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T10:25:14.176811Z"},"content_sha256":"eecf407ee4f0516295069440de2f15c70b37c1aa18284f06fcbe99e17d7a25bc","schema_version":"1.0","event_id":"sha256:eecf407ee4f0516295069440de2f15c70b37c1aa18284f06fcbe99e17d7a25bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:V5BO3PICUDV5LWCUTXJXFCUAZU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Prequential MDL for Causal Structure Learning with Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alan Malek, Jorg Bornschein, Rosemary Nan Ke, Silvia Chiappa","submitted_at":"2021-07-02T22:35:21Z","abstract_excerpt":"Learning the structure of Bayesian networks and causal relationships from observations is a common goal in several areas of science and technology. We show that the prequential minimum description length principle (MDL) can be used to derive a practical scoring function for Bayesian networks when flexible and overparametrized neural networks are used to model the conditional probability distributions between observed variables. MDL represents an embodiment of Occam's Razor and we obtain plausible and parsimonious graph structures without relying on sparsity inducing priors or other regularizer"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.05481","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/2107.05481/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":"2026-07-05T02:57:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xj45d1YrVck/r1c7biSnxglZxXprYG7TXr1MqMY5gS0NXcF5WzEMovDQcx921FYzYrt2GkA4mBceBu0YUFkKBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T10:25:14.177181Z"},"content_sha256":"d9a85f135b3acfa9bd91643e3858d8fb4dfe2b806400a90143924327cb264f2a","schema_version":"1.0","event_id":"sha256:d9a85f135b3acfa9bd91643e3858d8fb4dfe2b806400a90143924327cb264f2a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V5BO3PICUDV5LWCUTXJXFCUAZU/bundle.json","state_url":"https://pith.science/pith/V5BO3PICUDV5LWCUTXJXFCUAZU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V5BO3PICUDV5LWCUTXJXFCUAZU/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":"2026-07-07T10:25:14Z","links":{"resolver":"https://pith.science/pith/V5BO3PICUDV5LWCUTXJXFCUAZU","bundle":"https://pith.science/pith/V5BO3PICUDV5LWCUTXJXFCUAZU/bundle.json","state":"https://pith.science/pith/V5BO3PICUDV5LWCUTXJXFCUAZU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V5BO3PICUDV5LWCUTXJXFCUAZU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:V5BO3PICUDV5LWCUTXJXFCUAZU","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":"38adccc7c442b971d4d9a003868bbb094021278486eb543f29f67f4461741eb6","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-07-02T22:35:21Z","title_canon_sha256":"6cb1e14a09b739b25b59c827af1c72719e448216ceb1e87bd973c3707c170c4c"},"schema_version":"1.0","source":{"id":"2107.05481","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.05481","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"arxiv_version","alias_value":"2107.05481v1","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.05481","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"pith_short_12","alias_value":"V5BO3PICUDV5","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"pith_short_16","alias_value":"V5BO3PICUDV5LWCU","created_at":"2026-07-05T02:57:03Z"},{"alias_kind":"pith_short_8","alias_value":"V5BO3PIC","created_at":"2026-07-05T02:57:03Z"}],"graph_snapshots":[{"event_id":"sha256:d9a85f135b3acfa9bd91643e3858d8fb4dfe2b806400a90143924327cb264f2a","target":"graph","created_at":"2026-07-05T02:57:03Z","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/2107.05481/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning the structure of Bayesian networks and causal relationships from observations is a common goal in several areas of science and technology. We show that the prequential minimum description length principle (MDL) can be used to derive a practical scoring function for Bayesian networks when flexible and overparametrized neural networks are used to model the conditional probability distributions between observed variables. MDL represents an embodiment of Occam's Razor and we obtain plausible and parsimonious graph structures without relying on sparsity inducing priors or other regularizer","authors_text":"Alan Malek, Jorg Bornschein, Rosemary Nan Ke, Silvia Chiappa","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-07-02T22:35:21Z","title":"Prequential MDL for Causal Structure Learning with Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.05481","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:eecf407ee4f0516295069440de2f15c70b37c1aa18284f06fcbe99e17d7a25bc","target":"record","created_at":"2026-07-05T02:57:03Z","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":"38adccc7c442b971d4d9a003868bbb094021278486eb543f29f67f4461741eb6","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-07-02T22:35:21Z","title_canon_sha256":"6cb1e14a09b739b25b59c827af1c72719e448216ceb1e87bd973c3707c170c4c"},"schema_version":"1.0","source":{"id":"2107.05481","kind":"arxiv","version":1}},"canonical_sha256":"af42edbd02a0ebd5d8549dd3728a80cd0d07061866c5b97f230fdf399bad8be0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af42edbd02a0ebd5d8549dd3728a80cd0d07061866c5b97f230fdf399bad8be0","first_computed_at":"2026-07-05T02:57:03.261270Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:57:03.261270Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nQChnqZFjsQKrqx12nd8H9ltpgzaM9EVOpYxwVg2rMbf4wufK0EkhgfSHO6jI5Y2fu3IUSVUm1caZs4LO2tADQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:57:03.261607Z","signed_message":"canonical_sha256_bytes"},"source_id":"2107.05481","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eecf407ee4f0516295069440de2f15c70b37c1aa18284f06fcbe99e17d7a25bc","sha256:d9a85f135b3acfa9bd91643e3858d8fb4dfe2b806400a90143924327cb264f2a"],"state_sha256":"f17dccb54a4e50a65e96e0e62517fa6959a3d11bf29a3b944db60fc27dc49664"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"semGsiGKAMuKfL5SdkNcFWQtTijurrDnqmkFDYA+dpGiXt/w9iWK0yxqzelyvSvC8Jb7RLpRg5G/phZ6jnoCBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T10:25:14.179156Z","bundle_sha256":"872ed7eaf83fd024c0430acc5ce3ac3817777a0e33008c75c95a272edcc9143f"}}