{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:VTMRAKHZ7NRU7QQIPRKWZGVMV2","short_pith_number":"pith:VTMRAKHZ","schema_version":"1.0","canonical_sha256":"acd91028f9fb634fc2087c556c9aacaeb9d98342185752bb6dc4b7abceda8272","source":{"kind":"arxiv","id":"1511.00524","version":1},"attestation_state":"computed","paper":{"title":"Inverse Problems in a Bayesian Setting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.PR","authors_text":"Alexander Litvinenko, Bojana V. Rosi\\'c, Elmar Zander, Hermann G. Matthies, Oliver Pajonk","submitted_at":"2015-11-02T14:39:25Z","abstract_excerpt":"In a Bayesian setting, inverse problems and uncertainty quantification (UQ) --- the propagation of uncertainty through a computational (forward) model --- are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian"},"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":"1511.00524","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2015-11-02T14:39:25Z","cross_cats_sorted":[],"title_canon_sha256":"ea926a4cdd1dc22b41107b0392ee86fcf38dca20792ad530bfbae33b013702cb","abstract_canon_sha256":"be0bf5bb6315fdde811006c19483991888b1da2feaa3e397dd8b8fd9fa44ea87"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:28:12.101239Z","signature_b64":"872XdwejdanPiOG4FZtGfVIph+aFKDc3AItB58Cs0hacWOxGBJWlqVzdnhATg+FMY9ld4Li1DpFKJLFQF4xvBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"acd91028f9fb634fc2087c556c9aacaeb9d98342185752bb6dc4b7abceda8272","last_reissued_at":"2026-05-18T01:28:12.100595Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:28:12.100595Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Inverse Problems in a Bayesian Setting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.PR","authors_text":"Alexander Litvinenko, Bojana V. Rosi\\'c, Elmar Zander, Hermann G. Matthies, Oliver Pajonk","submitted_at":"2015-11-02T14:39:25Z","abstract_excerpt":"In a Bayesian setting, inverse problems and uncertainty quantification (UQ) --- the propagation of uncertainty through a computational (forward) model --- are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.00524","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":""},"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":"1511.00524","created_at":"2026-05-18T01:28:12.100679+00:00"},{"alias_kind":"arxiv_version","alias_value":"1511.00524v1","created_at":"2026-05-18T01:28:12.100679+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.00524","created_at":"2026-05-18T01:28:12.100679+00:00"},{"alias_kind":"pith_short_12","alias_value":"VTMRAKHZ7NRU","created_at":"2026-05-18T12:29:47.479230+00:00"},{"alias_kind":"pith_short_16","alias_value":"VTMRAKHZ7NRU7QQI","created_at":"2026-05-18T12:29:47.479230+00:00"},{"alias_kind":"pith_short_8","alias_value":"VTMRAKHZ","created_at":"2026-05-18T12:29:47.479230+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/VTMRAKHZ7NRU7QQIPRKWZGVMV2","json":"https://pith.science/pith/VTMRAKHZ7NRU7QQIPRKWZGVMV2.json","graph_json":"https://pith.science/api/pith-number/VTMRAKHZ7NRU7QQIPRKWZGVMV2/graph.json","events_json":"https://pith.science/api/pith-number/VTMRAKHZ7NRU7QQIPRKWZGVMV2/events.json","paper":"https://pith.science/paper/VTMRAKHZ"},"agent_actions":{"view_html":"https://pith.science/pith/VTMRAKHZ7NRU7QQIPRKWZGVMV2","download_json":"https://pith.science/pith/VTMRAKHZ7NRU7QQIPRKWZGVMV2.json","view_paper":"https://pith.science/paper/VTMRAKHZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1511.00524&json=true","fetch_graph":"https://pith.science/api/pith-number/VTMRAKHZ7NRU7QQIPRKWZGVMV2/graph.json","fetch_events":"https://pith.science/api/pith-number/VTMRAKHZ7NRU7QQIPRKWZGVMV2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VTMRAKHZ7NRU7QQIPRKWZGVMV2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VTMRAKHZ7NRU7QQIPRKWZGVMV2/action/storage_attestation","attest_author":"https://pith.science/pith/VTMRAKHZ7NRU7QQIPRKWZGVMV2/action/author_attestation","sign_citation":"https://pith.science/pith/VTMRAKHZ7NRU7QQIPRKWZGVMV2/action/citation_signature","submit_replication":"https://pith.science/pith/VTMRAKHZ7NRU7QQIPRKWZGVMV2/action/replication_record"}},"created_at":"2026-05-18T01:28:12.100679+00:00","updated_at":"2026-05-18T01:28:12.100679+00:00"}