{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:QYVOIB5RC5VEI25UUOWVQVFEIO","short_pith_number":"pith:QYVOIB5R","schema_version":"1.0","canonical_sha256":"862ae407b1176a446bb4a3ad5854a44391dd7dabf8b5de926f5f363ca5563c47","source":{"kind":"arxiv","id":"2307.13918","version":3},"attestation_state":"computed","paper":{"title":"Simulation-based Inference for Cardiovascular Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","q-bio.QM"],"primary_cat":"stat.ML","authors_text":"Andrew C. Miller, Antoine Wehenkel, Guillermo Sapiro, Jens Behrmann, J\\\"orn-Henrik Jacobsen, Laura Manduchi, Luca Pegolotti, Marco Cuturi, Ozan Sener","submitted_at":"2023-07-26T02:34:57Z","abstract_excerpt":"Over the past decades, hemodynamics simulators have steadily evolved and have become tools of choice for studying cardiovascular systems in-silico. While such tools are routinely used to simulate whole-body hemodynamics from physiological parameters, solving the corresponding inverse problem of mapping waveforms back to plausible physiological parameters remains both promising and challenging. Motivated by advances in simulation-based inference (SBI), we cast this inverse problem as statistical inference. In contrast to alternative approaches, SBI provides \\textit{posterior distributions} for "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2307.13918","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2023-07-26T02:34:57Z","cross_cats_sorted":["cs.LG","q-bio.QM"],"title_canon_sha256":"d73d50ddb6ad806e0856aebc6748e94b2553c7ac6ddd7f2b92f0476e30090709","abstract_canon_sha256":"a77db4c65c02bb9a84a09e562a3e71a46060027adc44df0de7fa3a1a77e5cdc7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:55:06.452010Z","signature_b64":"aQ4+GrQ0OZUu0mmSzEgu4IBSNhQQs6TJtksmDslPK3rq/u8nGrt9gKclgfySplXW12Bdm/TveP+QWniGYrEYBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"862ae407b1176a446bb4a3ad5854a44391dd7dabf8b5de926f5f363ca5563c47","last_reissued_at":"2026-07-05T09:55:06.451429Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:55:06.451429Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Simulation-based Inference for Cardiovascular Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","q-bio.QM"],"primary_cat":"stat.ML","authors_text":"Andrew C. Miller, Antoine Wehenkel, Guillermo Sapiro, Jens Behrmann, J\\\"orn-Henrik Jacobsen, Laura Manduchi, Luca Pegolotti, Marco Cuturi, Ozan Sener","submitted_at":"2023-07-26T02:34:57Z","abstract_excerpt":"Over the past decades, hemodynamics simulators have steadily evolved and have become tools of choice for studying cardiovascular systems in-silico. While such tools are routinely used to simulate whole-body hemodynamics from physiological parameters, solving the corresponding inverse problem of mapping waveforms back to plausible physiological parameters remains both promising and challenging. Motivated by advances in simulation-based inference (SBI), we cast this inverse problem as statistical inference. In contrast to alternative approaches, SBI provides \\textit{posterior distributions} for "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.13918","kind":"arxiv","version":3},"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/2307.13918/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2307.13918","created_at":"2026-07-05T09:55:06.451497+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.13918v3","created_at":"2026-07-05T09:55:06.451497+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.13918","created_at":"2026-07-05T09:55:06.451497+00:00"},{"alias_kind":"pith_short_12","alias_value":"QYVOIB5RC5VE","created_at":"2026-07-05T09:55:06.451497+00:00"},{"alias_kind":"pith_short_16","alias_value":"QYVOIB5RC5VEI25U","created_at":"2026-07-05T09:55:06.451497+00:00"},{"alias_kind":"pith_short_8","alias_value":"QYVOIB5R","created_at":"2026-07-05T09:55:06.451497+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QYVOIB5RC5VEI25UUOWVQVFEIO","json":"https://pith.science/pith/QYVOIB5RC5VEI25UUOWVQVFEIO.json","graph_json":"https://pith.science/api/pith-number/QYVOIB5RC5VEI25UUOWVQVFEIO/graph.json","events_json":"https://pith.science/api/pith-number/QYVOIB5RC5VEI25UUOWVQVFEIO/events.json","paper":"https://pith.science/paper/QYVOIB5R"},"agent_actions":{"view_html":"https://pith.science/pith/QYVOIB5RC5VEI25UUOWVQVFEIO","download_json":"https://pith.science/pith/QYVOIB5RC5VEI25UUOWVQVFEIO.json","view_paper":"https://pith.science/paper/QYVOIB5R","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.13918&json=true","fetch_graph":"https://pith.science/api/pith-number/QYVOIB5RC5VEI25UUOWVQVFEIO/graph.json","fetch_events":"https://pith.science/api/pith-number/QYVOIB5RC5VEI25UUOWVQVFEIO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QYVOIB5RC5VEI25UUOWVQVFEIO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QYVOIB5RC5VEI25UUOWVQVFEIO/action/storage_attestation","attest_author":"https://pith.science/pith/QYVOIB5RC5VEI25UUOWVQVFEIO/action/author_attestation","sign_citation":"https://pith.science/pith/QYVOIB5RC5VEI25UUOWVQVFEIO/action/citation_signature","submit_replication":"https://pith.science/pith/QYVOIB5RC5VEI25UUOWVQVFEIO/action/replication_record"}},"created_at":"2026-07-05T09:55:06.451497+00:00","updated_at":"2026-07-05T09:55:06.451497+00:00"}