{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:IAEQZBVBLBY5H2ZOPTWK747ANH","short_pith_number":"pith:IAEQZBVB","schema_version":"1.0","canonical_sha256":"40090c86a15871d3eb2e7cecaff3e069e5f54e5d5680b257d2bf1f74d53d1978","source":{"kind":"arxiv","id":"1602.08412","version":1},"attestation_state":"computed","paper":{"title":"Fast inference of ill-posed problems within a convex space","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.dis-nn","cond-mat.stat-mech","q-bio.MN"],"primary_cat":"cs.OH","authors_text":"Jorge Fernandez-De-Cossio-Diaz, Roberto Mulet","submitted_at":"2016-02-01T13:45:50Z","abstract_excerpt":"In multiple scientific and technological applications we face the problem of having low dimensional data to be justified by a linear model defined in a high dimensional parameter space. The difference in dimensionality makes the problem ill-defined: the model is consistent with the data for many values of its parameters. The objective is to find the probability distribution of parameter values consistent with the data, a problem that can be cast as the exploration of a high dimensional convex polytope. In this work we introduce a novel algorithm to solve this problem efficiently. It provides r"},"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":"1602.08412","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.OH","submitted_at":"2016-02-01T13:45:50Z","cross_cats_sorted":["cond-mat.dis-nn","cond-mat.stat-mech","q-bio.MN"],"title_canon_sha256":"e67aed59e292de78fd4c2aae6e88a11d5d58de8370a21fbd44472e9e630882a7","abstract_canon_sha256":"602a2daab166bb02f0cafd3c67cbe2af36f60a9fffbe0e0eda62039eeda56ba7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:09:57.625631Z","signature_b64":"XjxaOMcfDkuGd8ZpJt4OdUiR1piV/VALTF9Xqu45cAw/BnwdmCQhBHuSO46QkOq+byRIXTD/8rL7yq9jXBJoAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40090c86a15871d3eb2e7cecaff3e069e5f54e5d5680b257d2bf1f74d53d1978","last_reissued_at":"2026-05-18T01:09:57.624944Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:09:57.624944Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fast inference of ill-posed problems within a convex space","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.dis-nn","cond-mat.stat-mech","q-bio.MN"],"primary_cat":"cs.OH","authors_text":"Jorge Fernandez-De-Cossio-Diaz, Roberto Mulet","submitted_at":"2016-02-01T13:45:50Z","abstract_excerpt":"In multiple scientific and technological applications we face the problem of having low dimensional data to be justified by a linear model defined in a high dimensional parameter space. The difference in dimensionality makes the problem ill-defined: the model is consistent with the data for many values of its parameters. The objective is to find the probability distribution of parameter values consistent with the data, a problem that can be cast as the exploration of a high dimensional convex polytope. In this work we introduce a novel algorithm to solve this problem efficiently. It provides r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.08412","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":"1602.08412","created_at":"2026-05-18T01:09:57.625044+00:00"},{"alias_kind":"arxiv_version","alias_value":"1602.08412v1","created_at":"2026-05-18T01:09:57.625044+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.08412","created_at":"2026-05-18T01:09:57.625044+00:00"},{"alias_kind":"pith_short_12","alias_value":"IAEQZBVBLBY5","created_at":"2026-05-18T12:30:22.444734+00:00"},{"alias_kind":"pith_short_16","alias_value":"IAEQZBVBLBY5H2ZO","created_at":"2026-05-18T12:30:22.444734+00:00"},{"alias_kind":"pith_short_8","alias_value":"IAEQZBVB","created_at":"2026-05-18T12:30:22.444734+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/IAEQZBVBLBY5H2ZOPTWK747ANH","json":"https://pith.science/pith/IAEQZBVBLBY5H2ZOPTWK747ANH.json","graph_json":"https://pith.science/api/pith-number/IAEQZBVBLBY5H2ZOPTWK747ANH/graph.json","events_json":"https://pith.science/api/pith-number/IAEQZBVBLBY5H2ZOPTWK747ANH/events.json","paper":"https://pith.science/paper/IAEQZBVB"},"agent_actions":{"view_html":"https://pith.science/pith/IAEQZBVBLBY5H2ZOPTWK747ANH","download_json":"https://pith.science/pith/IAEQZBVBLBY5H2ZOPTWK747ANH.json","view_paper":"https://pith.science/paper/IAEQZBVB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1602.08412&json=true","fetch_graph":"https://pith.science/api/pith-number/IAEQZBVBLBY5H2ZOPTWK747ANH/graph.json","fetch_events":"https://pith.science/api/pith-number/IAEQZBVBLBY5H2ZOPTWK747ANH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IAEQZBVBLBY5H2ZOPTWK747ANH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IAEQZBVBLBY5H2ZOPTWK747ANH/action/storage_attestation","attest_author":"https://pith.science/pith/IAEQZBVBLBY5H2ZOPTWK747ANH/action/author_attestation","sign_citation":"https://pith.science/pith/IAEQZBVBLBY5H2ZOPTWK747ANH/action/citation_signature","submit_replication":"https://pith.science/pith/IAEQZBVBLBY5H2ZOPTWK747ANH/action/replication_record"}},"created_at":"2026-05-18T01:09:57.625044+00:00","updated_at":"2026-05-18T01:09:57.625044+00:00"}