{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:5SUSOQ6EZRQKHUOEHTIN3EQEON","short_pith_number":"pith:5SUSOQ6E","canonical_record":{"source":{"id":"2004.14954","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2020-04-30T17:03:00Z","cross_cats_sorted":["cs.LG","stat.ML","stat.TH"],"title_canon_sha256":"04148940fab913f5fdaf8da81692e3efbe308777c23a0e00e38321e24f529cd3","abstract_canon_sha256":"120dcac7144bf79d2a06ccb7c1a21f3aad07dd5c78dd59b0c94c0416174c1276"},"schema_version":"1.0"},"canonical_sha256":"eca92743c4cc60a3d1c43cd0dd920473765190ea73eae3aa48a08c827e909532","source":{"kind":"arxiv","id":"2004.14954","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.14954","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"arxiv_version","alias_value":"2004.14954v1","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.14954","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"pith_short_12","alias_value":"5SUSOQ6EZRQK","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"pith_short_16","alias_value":"5SUSOQ6EZRQKHUOE","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"pith_short_8","alias_value":"5SUSOQ6E","created_at":"2026-07-05T00:59:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:5SUSOQ6EZRQKHUOEHTIN3EQEON","target":"record","payload":{"canonical_record":{"source":{"id":"2004.14954","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2020-04-30T17:03:00Z","cross_cats_sorted":["cs.LG","stat.ML","stat.TH"],"title_canon_sha256":"04148940fab913f5fdaf8da81692e3efbe308777c23a0e00e38321e24f529cd3","abstract_canon_sha256":"120dcac7144bf79d2a06ccb7c1a21f3aad07dd5c78dd59b0c94c0416174c1276"},"schema_version":"1.0"},"canonical_sha256":"eca92743c4cc60a3d1c43cd0dd920473765190ea73eae3aa48a08c827e909532","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:59:31.444196Z","signature_b64":"4fF/FDduluTe8X7EhvVv/B1kzXEwYasMBZ05tvCq1wo5C5pgQUvxLEAOXk3SQJ/CLojFVl0U+n2ny1cujHsPAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eca92743c4cc60a3d1c43cd0dd920473765190ea73eae3aa48a08c827e909532","last_reissued_at":"2026-07-05T00:59:31.443866Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:59:31.443866Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.14954","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":"2026-07-05T00:59:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TjTOydwEddkn/k/luQ7D7Q0BPysdZbI/EOzTg68otfv0YxvlDPJoob37jlBxM3z4BVGNC2MzBhPxsPA0ogRmDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T19:59:09.295757Z"},"content_sha256":"c07631428428ae08b00b15024688b97e19dee93820c1e1334c1e30511f225980","schema_version":"1.0","event_id":"sha256:c07631428428ae08b00b15024688b97e19dee93820c1e1334c1e30511f225980"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:5SUSOQ6EZRQKHUOEHTIN3EQEON","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On Deep Instrumental Variables Estimate","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML","stat.TH"],"primary_cat":"math.ST","authors_text":"Guang Cheng, Ruiqi Liu, Zuofeng Shang","submitted_at":"2020-04-30T17:03:00Z","abstract_excerpt":"The endogeneity issue is fundamentally important as many empirical applications may suffer from the omission of explanatory variables, measurement error, or simultaneous causality. Recently, \\cite{hllt17} propose a \"Deep Instrumental Variable (IV)\" framework based on deep neural networks to address endogeneity, demonstrating superior performances than existing approaches. The aim of this paper is to theoretically understand the empirical success of the Deep IV. Specifically, we consider a two-stage estimator using deep neural networks in the linear instrumental variables model. By imposing a l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.14954","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/2004.14954/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":"2026-07-05T00:59:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xpw1GDXEhh2fxXFkf1WlkLpf0UR3/+fNOcpIhjE2BhdX89/LnDFBoBRAphbPKBifgpRzRoSk43zSOnPhpz7QBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T19:59:09.296362Z"},"content_sha256":"71df35b11c917e5011744a3a9daf8cf6825026060c921e1369057327e06bf000","schema_version":"1.0","event_id":"sha256:71df35b11c917e5011744a3a9daf8cf6825026060c921e1369057327e06bf000"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5SUSOQ6EZRQKHUOEHTIN3EQEON/bundle.json","state_url":"https://pith.science/pith/5SUSOQ6EZRQKHUOEHTIN3EQEON/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5SUSOQ6EZRQKHUOEHTIN3EQEON/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":"2026-08-19T19:59:09Z","links":{"resolver":"https://pith.science/pith/5SUSOQ6EZRQKHUOEHTIN3EQEON","bundle":"https://pith.science/pith/5SUSOQ6EZRQKHUOEHTIN3EQEON/bundle.json","state":"https://pith.science/pith/5SUSOQ6EZRQKHUOEHTIN3EQEON/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5SUSOQ6EZRQKHUOEHTIN3EQEON/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:5SUSOQ6EZRQKHUOEHTIN3EQEON","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":"120dcac7144bf79d2a06ccb7c1a21f3aad07dd5c78dd59b0c94c0416174c1276","cross_cats_sorted":["cs.LG","stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2020-04-30T17:03:00Z","title_canon_sha256":"04148940fab913f5fdaf8da81692e3efbe308777c23a0e00e38321e24f529cd3"},"schema_version":"1.0","source":{"id":"2004.14954","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.14954","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"arxiv_version","alias_value":"2004.14954v1","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.14954","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"pith_short_12","alias_value":"5SUSOQ6EZRQK","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"pith_short_16","alias_value":"5SUSOQ6EZRQKHUOE","created_at":"2026-07-05T00:59:31Z"},{"alias_kind":"pith_short_8","alias_value":"5SUSOQ6E","created_at":"2026-07-05T00:59:31Z"}],"graph_snapshots":[{"event_id":"sha256:71df35b11c917e5011744a3a9daf8cf6825026060c921e1369057327e06bf000","target":"graph","created_at":"2026-07-05T00:59:31Z","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/2004.14954/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The endogeneity issue is fundamentally important as many empirical applications may suffer from the omission of explanatory variables, measurement error, or simultaneous causality. Recently, \\cite{hllt17} propose a \"Deep Instrumental Variable (IV)\" framework based on deep neural networks to address endogeneity, demonstrating superior performances than existing approaches. The aim of this paper is to theoretically understand the empirical success of the Deep IV. Specifically, we consider a two-stage estimator using deep neural networks in the linear instrumental variables model. By imposing a l","authors_text":"Guang Cheng, Ruiqi Liu, Zuofeng Shang","cross_cats":["cs.LG","stat.ML","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2020-04-30T17:03:00Z","title":"On Deep Instrumental Variables Estimate"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.14954","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:c07631428428ae08b00b15024688b97e19dee93820c1e1334c1e30511f225980","target":"record","created_at":"2026-07-05T00:59:31Z","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":"120dcac7144bf79d2a06ccb7c1a21f3aad07dd5c78dd59b0c94c0416174c1276","cross_cats_sorted":["cs.LG","stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2020-04-30T17:03:00Z","title_canon_sha256":"04148940fab913f5fdaf8da81692e3efbe308777c23a0e00e38321e24f529cd3"},"schema_version":"1.0","source":{"id":"2004.14954","kind":"arxiv","version":1}},"canonical_sha256":"eca92743c4cc60a3d1c43cd0dd920473765190ea73eae3aa48a08c827e909532","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eca92743c4cc60a3d1c43cd0dd920473765190ea73eae3aa48a08c827e909532","first_computed_at":"2026-07-05T00:59:31.443866Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:59:31.443866Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4fF/FDduluTe8X7EhvVv/B1kzXEwYasMBZ05tvCq1wo5C5pgQUvxLEAOXk3SQJ/CLojFVl0U+n2ny1cujHsPAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:59:31.444196Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.14954","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c07631428428ae08b00b15024688b97e19dee93820c1e1334c1e30511f225980","sha256:71df35b11c917e5011744a3a9daf8cf6825026060c921e1369057327e06bf000"],"state_sha256":"b9cbbd2df269340fb598b2af7c3e83759433a012a51ce35b5b0bff6a2a40f136"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I4v1htsDNhqex0fiVh+yO11Td+//Z4pBV/x8NwAtsQ8kC8PLS1GzCEpDly3XtplqLKxpaJ7CquSxVrLkBYZ7AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T19:59:09.300738Z","bundle_sha256":"f9e4deb0a092a05f965c9ce1f84c56e8f2c5b8f095f81170738d8e4356c1863a"}}