{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:6OKZC7GNKFR34RBQJYEOCT7OIC","short_pith_number":"pith:6OKZC7GN","canonical_record":{"source":{"id":"2001.05486","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2020-01-15T18:56:57Z","cross_cats_sorted":["cs.LG","hep-ph","stat.ML"],"title_canon_sha256":"51ed32d91478fcba96358d65ae4bd53435839d57b4e56b6eae4c789f254a4eb7","abstract_canon_sha256":"5d395077a43995c4b82e1744a80f8b6844f9def09081f0c4161f27ce0e2e768c"},"schema_version":"1.0"},"canonical_sha256":"f395917ccd5163be44304e08e14fee40aec4c25d46a5fb8bdc4c3f83079de2d0","source":{"kind":"arxiv","id":"2001.05486","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.05486","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"arxiv_version","alias_value":"2001.05486v2","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.05486","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"pith_short_12","alias_value":"6OKZC7GNKFR3","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"pith_short_16","alias_value":"6OKZC7GNKFR34RBQ","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"pith_short_8","alias_value":"6OKZC7GN","created_at":"2026-07-05T01:27:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:6OKZC7GNKFR34RBQJYEOCT7OIC","target":"record","payload":{"canonical_record":{"source":{"id":"2001.05486","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2020-01-15T18:56:57Z","cross_cats_sorted":["cs.LG","hep-ph","stat.ML"],"title_canon_sha256":"51ed32d91478fcba96358d65ae4bd53435839d57b4e56b6eae4c789f254a4eb7","abstract_canon_sha256":"5d395077a43995c4b82e1744a80f8b6844f9def09081f0c4161f27ce0e2e768c"},"schema_version":"1.0"},"canonical_sha256":"f395917ccd5163be44304e08e14fee40aec4c25d46a5fb8bdc4c3f83079de2d0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:27:44.588844Z","signature_b64":"vz2s+NrIBRZMz6FkU1HlzKUATsDKu/9xiJfuiYUtMlHNNtcKO22BTECSiyvirGy39e4MTXHEylromRhmbqhxDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f395917ccd5163be44304e08e14fee40aec4c25d46a5fb8bdc4c3f83079de2d0","last_reissued_at":"2026-07-05T01:27:44.588274Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:27:44.588274Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2001.05486","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":"2026-07-05T01:27:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y7rCKw0q3XA0zko6U5j/H/XeySI3ZXFFY2kYwYXuxctOEkPpGBp9IcV/KSeLn/qT48IdJAHZQKsIbFt8U9RlDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T23:22:22.604979Z"},"content_sha256":"0f9954c955f76e815e75e5773641d24d93356a40323d39ee1df598d56a0b42ca","schema_version":"1.0","event_id":"sha256:0f9954c955f76e815e75e5773641d24d93356a40323d39ee1df598d56a0b42ca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:6OKZC7GNKFR34RBQJYEOCT7OIC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"i-flow: High-dimensional Integration and Sampling with Normalizing Flows","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","hep-ph","stat.ML"],"primary_cat":"physics.comp-ph","authors_text":"Christina Gao, Claudius Krause, Joshua Isaacson","submitted_at":"2020-01-15T18:56:57Z","abstract_excerpt":"In many fields of science, high-dimensional integration is required. Numerical methods have been developed to evaluate these complex integrals. We introduce the code i-flow, a python package that performs high-dimensional numerical integration utilizing normalizing flows. Normalizing flows are machine-learned, bijective mappings between two distributions. i-flow can also be used to sample random points according to complicated distributions in high dimensions. We compare i-flow to other algorithms for high-dimensional numerical integration and show that i-flow outperforms them for high dimensi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.05486","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/2001.05486/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":"2026-07-05T01:27:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WMWsiN9fXbrjF6hY68Pckr1kcTJFFdiqTOSLggn0Zgi1S8dgrTe1Q3NfGkXMKptyoOa7UiUhl4w4wLq6X8PGAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T23:22:22.605489Z"},"content_sha256":"534809d8efdf785e3378dc653296a38966063a29fd50dd86ef3b96db319c1a34","schema_version":"1.0","event_id":"sha256:534809d8efdf785e3378dc653296a38966063a29fd50dd86ef3b96db319c1a34"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6OKZC7GNKFR34RBQJYEOCT7OIC/bundle.json","state_url":"https://pith.science/pith/6OKZC7GNKFR34RBQJYEOCT7OIC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6OKZC7GNKFR34RBQJYEOCT7OIC/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":"2026-08-03T23:22:22Z","links":{"resolver":"https://pith.science/pith/6OKZC7GNKFR34RBQJYEOCT7OIC","bundle":"https://pith.science/pith/6OKZC7GNKFR34RBQJYEOCT7OIC/bundle.json","state":"https://pith.science/pith/6OKZC7GNKFR34RBQJYEOCT7OIC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6OKZC7GNKFR34RBQJYEOCT7OIC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:6OKZC7GNKFR34RBQJYEOCT7OIC","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":"5d395077a43995c4b82e1744a80f8b6844f9def09081f0c4161f27ce0e2e768c","cross_cats_sorted":["cs.LG","hep-ph","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2020-01-15T18:56:57Z","title_canon_sha256":"51ed32d91478fcba96358d65ae4bd53435839d57b4e56b6eae4c789f254a4eb7"},"schema_version":"1.0","source":{"id":"2001.05486","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.05486","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"arxiv_version","alias_value":"2001.05486v2","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.05486","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"pith_short_12","alias_value":"6OKZC7GNKFR3","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"pith_short_16","alias_value":"6OKZC7GNKFR34RBQ","created_at":"2026-07-05T01:27:44Z"},{"alias_kind":"pith_short_8","alias_value":"6OKZC7GN","created_at":"2026-07-05T01:27:44Z"}],"graph_snapshots":[{"event_id":"sha256:534809d8efdf785e3378dc653296a38966063a29fd50dd86ef3b96db319c1a34","target":"graph","created_at":"2026-07-05T01:27:44Z","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/2001.05486/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In many fields of science, high-dimensional integration is required. Numerical methods have been developed to evaluate these complex integrals. We introduce the code i-flow, a python package that performs high-dimensional numerical integration utilizing normalizing flows. Normalizing flows are machine-learned, bijective mappings between two distributions. i-flow can also be used to sample random points according to complicated distributions in high dimensions. We compare i-flow to other algorithms for high-dimensional numerical integration and show that i-flow outperforms them for high dimensi","authors_text":"Christina Gao, Claudius Krause, Joshua Isaacson","cross_cats":["cs.LG","hep-ph","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2020-01-15T18:56:57Z","title":"i-flow: High-dimensional Integration and Sampling with Normalizing Flows"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.05486","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":"sha256:0f9954c955f76e815e75e5773641d24d93356a40323d39ee1df598d56a0b42ca","target":"record","created_at":"2026-07-05T01:27:44Z","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":"5d395077a43995c4b82e1744a80f8b6844f9def09081f0c4161f27ce0e2e768c","cross_cats_sorted":["cs.LG","hep-ph","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2020-01-15T18:56:57Z","title_canon_sha256":"51ed32d91478fcba96358d65ae4bd53435839d57b4e56b6eae4c789f254a4eb7"},"schema_version":"1.0","source":{"id":"2001.05486","kind":"arxiv","version":2}},"canonical_sha256":"f395917ccd5163be44304e08e14fee40aec4c25d46a5fb8bdc4c3f83079de2d0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f395917ccd5163be44304e08e14fee40aec4c25d46a5fb8bdc4c3f83079de2d0","first_computed_at":"2026-07-05T01:27:44.588274Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:27:44.588274Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vz2s+NrIBRZMz6FkU1HlzKUATsDKu/9xiJfuiYUtMlHNNtcKO22BTECSiyvirGy39e4MTXHEylromRhmbqhxDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:27:44.588844Z","signed_message":"canonical_sha256_bytes"},"source_id":"2001.05486","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0f9954c955f76e815e75e5773641d24d93356a40323d39ee1df598d56a0b42ca","sha256:534809d8efdf785e3378dc653296a38966063a29fd50dd86ef3b96db319c1a34"],"state_sha256":"30a1b9b061fb68589b7ac8996041d898ad455ca82f44094c83047d83efc83060"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n1DsIgSceRu4bF665tXHsROI7l0iMeu0aEyRdvI6zBkvNBZbrDAqWAAyq8YeoRd9rUhAvwe2lyw1yPnUr4tVDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T23:22:22.608976Z","bundle_sha256":"0e7da7c44f7882594711528ba2b5ae32ba587d386ed8f46c03fa6c8e916187f7"}}