{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:74VQJPDU2TE42PPMAQ437ATL5V","short_pith_number":"pith:74VQJPDU","canonical_record":{"source":{"id":"2110.14690","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2021-10-27T18:16:39Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5c7f6ff0fe97a153c7ffbb5612b6dd65f071038b3886dcd6b64dae0ed85b1285","abstract_canon_sha256":"1eeae0c8ea5f806b5341c939df66756c078acc6cec776b3f466204de2967b064"},"schema_version":"1.0"},"canonical_sha256":"ff2b04bc74d4c9cd3dec0439bf826bed7a20710561343a67e118213c26e0f0c3","source":{"kind":"arxiv","id":"2110.14690","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.14690","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"arxiv_version","alias_value":"2110.14690v1","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.14690","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"pith_short_12","alias_value":"74VQJPDU2TE4","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"pith_short_16","alias_value":"74VQJPDU2TE42PPM","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"pith_short_8","alias_value":"74VQJPDU","created_at":"2026-07-05T03:26:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:74VQJPDU2TE42PPMAQ437ATL5V","target":"record","payload":{"canonical_record":{"source":{"id":"2110.14690","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2021-10-27T18:16:39Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5c7f6ff0fe97a153c7ffbb5612b6dd65f071038b3886dcd6b64dae0ed85b1285","abstract_canon_sha256":"1eeae0c8ea5f806b5341c939df66756c078acc6cec776b3f466204de2967b064"},"schema_version":"1.0"},"canonical_sha256":"ff2b04bc74d4c9cd3dec0439bf826bed7a20710561343a67e118213c26e0f0c3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:26:46.282365Z","signature_b64":"Kwb/NUIjq85R6UxVJVCgJ/2oTrF/9cFEA0teskPYLa+yqGrlhbwor8XqZljs2kgMrMNvUd3XQf15vN+lkpBMCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ff2b04bc74d4c9cd3dec0439bf826bed7a20710561343a67e118213c26e0f0c3","last_reissued_at":"2026-07-05T03:26:46.281905Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:26:46.281905Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.14690","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":"2026-07-05T03:26:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xdn4Td/bwLPOgkm7ZqS90HHgH1KPpGs22OJJNO7KSTA5pOAiR1TXSKAc5PZNjkGJarBpdSkA4tPiC+d2xqpJDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:21:16.734962Z"},"content_sha256":"d3e2b03d966c933101d870da7ef29b515c157d61334d3ca17124bd91f2a1eb0b","schema_version":"1.0","event_id":"sha256:d3e2b03d966c933101d870da7ef29b515c157d61334d3ca17124bd91f2a1eb0b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:74VQJPDU2TE42PPMAQ437ATL5V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Isabel Valera, Miriam Rateike, Pablo Sanchez-Martin","submitted_at":"2021-10-27T18:16:39Z","abstract_excerpt":"In this paper, we introduce VACA, a novel class of variational graph autoencoders for causal inference in the absence of hidden confounders, when only observational data and the causal graph are available. Without making any parametric assumptions, VACA mimics the necessary properties of a Structural Causal Model (SCM) to provide a flexible and practical framework for approximating interventions (do-operator) and abduction-action-prediction steps. As a result, and as shown by our empirical results, VACA accurately approximates the interventional and counterfactual distributions on diverse SCMs"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.14690","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/2110.14690/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":"2026-07-05T03:26:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZEzkSbNrq2fO50jBf/OxCrBNpz0+YPlY+7ZPJaKJQF0SmK/lLQ3GV4KyBC36h8G/EjxmuA23bnRH0xB9CZ9XAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:21:16.735522Z"},"content_sha256":"57db3301698599e31542745918942c6184f6ca5f75ed349223ee606cf3d2eeb1","schema_version":"1.0","event_id":"sha256:57db3301698599e31542745918942c6184f6ca5f75ed349223ee606cf3d2eeb1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/74VQJPDU2TE42PPMAQ437ATL5V/bundle.json","state_url":"https://pith.science/pith/74VQJPDU2TE42PPMAQ437ATL5V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/74VQJPDU2TE42PPMAQ437ATL5V/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":"2026-08-08T20:21:16Z","links":{"resolver":"https://pith.science/pith/74VQJPDU2TE42PPMAQ437ATL5V","bundle":"https://pith.science/pith/74VQJPDU2TE42PPMAQ437ATL5V/bundle.json","state":"https://pith.science/pith/74VQJPDU2TE42PPMAQ437ATL5V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/74VQJPDU2TE42PPMAQ437ATL5V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:74VQJPDU2TE42PPMAQ437ATL5V","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":"1eeae0c8ea5f806b5341c939df66756c078acc6cec776b3f466204de2967b064","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2021-10-27T18:16:39Z","title_canon_sha256":"5c7f6ff0fe97a153c7ffbb5612b6dd65f071038b3886dcd6b64dae0ed85b1285"},"schema_version":"1.0","source":{"id":"2110.14690","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.14690","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"arxiv_version","alias_value":"2110.14690v1","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.14690","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"pith_short_12","alias_value":"74VQJPDU2TE4","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"pith_short_16","alias_value":"74VQJPDU2TE42PPM","created_at":"2026-07-05T03:26:46Z"},{"alias_kind":"pith_short_8","alias_value":"74VQJPDU","created_at":"2026-07-05T03:26:46Z"}],"graph_snapshots":[{"event_id":"sha256:57db3301698599e31542745918942c6184f6ca5f75ed349223ee606cf3d2eeb1","target":"graph","created_at":"2026-07-05T03:26:46Z","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/2110.14690/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we introduce VACA, a novel class of variational graph autoencoders for causal inference in the absence of hidden confounders, when only observational data and the causal graph are available. Without making any parametric assumptions, VACA mimics the necessary properties of a Structural Causal Model (SCM) to provide a flexible and practical framework for approximating interventions (do-operator) and abduction-action-prediction steps. As a result, and as shown by our empirical results, VACA accurately approximates the interventional and counterfactual distributions on diverse SCMs","authors_text":"Isabel Valera, Miriam Rateike, Pablo Sanchez-Martin","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2021-10-27T18:16:39Z","title":"VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.14690","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:d3e2b03d966c933101d870da7ef29b515c157d61334d3ca17124bd91f2a1eb0b","target":"record","created_at":"2026-07-05T03:26:46Z","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":"1eeae0c8ea5f806b5341c939df66756c078acc6cec776b3f466204de2967b064","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2021-10-27T18:16:39Z","title_canon_sha256":"5c7f6ff0fe97a153c7ffbb5612b6dd65f071038b3886dcd6b64dae0ed85b1285"},"schema_version":"1.0","source":{"id":"2110.14690","kind":"arxiv","version":1}},"canonical_sha256":"ff2b04bc74d4c9cd3dec0439bf826bed7a20710561343a67e118213c26e0f0c3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff2b04bc74d4c9cd3dec0439bf826bed7a20710561343a67e118213c26e0f0c3","first_computed_at":"2026-07-05T03:26:46.281905Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:26:46.281905Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Kwb/NUIjq85R6UxVJVCgJ/2oTrF/9cFEA0teskPYLa+yqGrlhbwor8XqZljs2kgMrMNvUd3XQf15vN+lkpBMCw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:26:46.282365Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.14690","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d3e2b03d966c933101d870da7ef29b515c157d61334d3ca17124bd91f2a1eb0b","sha256:57db3301698599e31542745918942c6184f6ca5f75ed349223ee606cf3d2eeb1"],"state_sha256":"858f14b5087d277b0f9b1d8a2a7af4a5d794df0e73e006bff28d10cef00df28c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sJPp/S9bFoVsgXPAAgR0N9CGc5XZDqwZm3ReRUlxIvbLSJTXcndtI8GwXY/I6hUTGrNHDpKyhjGaclb7f5FWDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T20:21:16.740199Z","bundle_sha256":"4da5cf98809393e0017e82da7d4fe85d51e8b028e548631eba3870da8e3f2579"}}