{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:CXDLMGHVJIL5GWKOOEJV4N3MFU","short_pith_number":"pith:CXDLMGHV","schema_version":"1.0","canonical_sha256":"15c6b618f54a17d3594e71135e376c2d331cb51a40e862a793623c228c731a0e","source":{"kind":"arxiv","id":"1804.08609","version":4},"attestation_state":"computed","paper":{"title":"A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.comp-ph"],"primary_cat":"math.NA","authors_text":"Huan Lei, Jing Li, Nathan Baker, Panos Stinis, Peiyuan Gao","submitted_at":"2018-04-20T20:59:23Z","abstract_excerpt":"The challenge of quantifying uncertainty propagation in real-world systems is rooted in the high-dimensionality of the stochastic input and the frequent lack of explicit knowledge of its probability distribution. Traditional approaches show limitations for such problems. To address these difficulties, we have developed a general framework of constructing surrogate models on spaces of stochastic input with arbitrary probability measure irrespective of the mutual dependencies between individual components and the analytical form. The present Data-driven Sparsity-enhancing Rotation for Arbitrary "},"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":"1804.08609","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2018-04-20T20:59:23Z","cross_cats_sorted":["physics.comp-ph"],"title_canon_sha256":"fb11e7bbb93575a85de22d2e999303a9c411caec888ee080c41c1115df740fc7","abstract_canon_sha256":"d0261df77c8fe14bae9cf20425dc82aaf7358e4e3e3885e6bfa29ba9248ea45f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:21.013028Z","signature_b64":"FnWDgvGkPVUrKHoqJLvVS1t/W34HwF/kiRHKIp02Wca+Nh8uFyP6LmBORaPPjtdwiC4iI4BzdDbyLIvAKVGHBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"15c6b618f54a17d3594e71135e376c2d331cb51a40e862a793623c228c731a0e","last_reissued_at":"2026-05-17T23:47:21.012456Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:21.012456Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.comp-ph"],"primary_cat":"math.NA","authors_text":"Huan Lei, Jing Li, Nathan Baker, Panos Stinis, Peiyuan Gao","submitted_at":"2018-04-20T20:59:23Z","abstract_excerpt":"The challenge of quantifying uncertainty propagation in real-world systems is rooted in the high-dimensionality of the stochastic input and the frequent lack of explicit knowledge of its probability distribution. Traditional approaches show limitations for such problems. To address these difficulties, we have developed a general framework of constructing surrogate models on spaces of stochastic input with arbitrary probability measure irrespective of the mutual dependencies between individual components and the analytical form. The present Data-driven Sparsity-enhancing Rotation for Arbitrary "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.08609","kind":"arxiv","version":4},"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":"1804.08609","created_at":"2026-05-17T23:47:21.012531+00:00"},{"alias_kind":"arxiv_version","alias_value":"1804.08609v4","created_at":"2026-05-17T23:47:21.012531+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.08609","created_at":"2026-05-17T23:47:21.012531+00:00"},{"alias_kind":"pith_short_12","alias_value":"CXDLMGHVJIL5","created_at":"2026-05-18T12:32:19.392346+00:00"},{"alias_kind":"pith_short_16","alias_value":"CXDLMGHVJIL5GWKO","created_at":"2026-05-18T12:32:19.392346+00:00"},{"alias_kind":"pith_short_8","alias_value":"CXDLMGHV","created_at":"2026-05-18T12:32:19.392346+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/CXDLMGHVJIL5GWKOOEJV4N3MFU","json":"https://pith.science/pith/CXDLMGHVJIL5GWKOOEJV4N3MFU.json","graph_json":"https://pith.science/api/pith-number/CXDLMGHVJIL5GWKOOEJV4N3MFU/graph.json","events_json":"https://pith.science/api/pith-number/CXDLMGHVJIL5GWKOOEJV4N3MFU/events.json","paper":"https://pith.science/paper/CXDLMGHV"},"agent_actions":{"view_html":"https://pith.science/pith/CXDLMGHVJIL5GWKOOEJV4N3MFU","download_json":"https://pith.science/pith/CXDLMGHVJIL5GWKOOEJV4N3MFU.json","view_paper":"https://pith.science/paper/CXDLMGHV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1804.08609&json=true","fetch_graph":"https://pith.science/api/pith-number/CXDLMGHVJIL5GWKOOEJV4N3MFU/graph.json","fetch_events":"https://pith.science/api/pith-number/CXDLMGHVJIL5GWKOOEJV4N3MFU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CXDLMGHVJIL5GWKOOEJV4N3MFU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CXDLMGHVJIL5GWKOOEJV4N3MFU/action/storage_attestation","attest_author":"https://pith.science/pith/CXDLMGHVJIL5GWKOOEJV4N3MFU/action/author_attestation","sign_citation":"https://pith.science/pith/CXDLMGHVJIL5GWKOOEJV4N3MFU/action/citation_signature","submit_replication":"https://pith.science/pith/CXDLMGHVJIL5GWKOOEJV4N3MFU/action/replication_record"}},"created_at":"2026-05-17T23:47:21.012531+00:00","updated_at":"2026-05-17T23:47:21.012531+00:00"}