{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QDQEXTGAF2FVUDX5VA3BXENOPI","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":"9a1d7bd983671f44976bea40b69bff018498765a87e4326e3d993fa871fb8f55","cross_cats_sorted":["cs.LG","math.PR","math.ST","stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2024-02-27T21:00:00Z","title_canon_sha256":"668fb795273ff0d79e3168f3b351fc1d3bdd3ef48693ad2bc1ff92dbbc4e2a1e"},"schema_version":"1.0","source":{"id":"2402.17886","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.17886","created_at":"2026-07-05T09:28:10Z"},{"alias_kind":"arxiv_version","alias_value":"2402.17886v4","created_at":"2026-07-05T09:28:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.17886","created_at":"2026-07-05T09:28:10Z"},{"alias_kind":"pith_short_12","alias_value":"QDQEXTGAF2FV","created_at":"2026-07-05T09:28:10Z"},{"alias_kind":"pith_short_16","alias_value":"QDQEXTGAF2FVUDX5","created_at":"2026-07-05T09:28:10Z"},{"alias_kind":"pith_short_8","alias_value":"QDQEXTGA","created_at":"2026-07-05T09:28:10Z"}],"graph_snapshots":[{"event_id":"sha256:7b337f1615aca87afdfbc375c3b695eaa3557a1ed4d767b770fbb9513e4cfbc7","target":"graph","created_at":"2026-07-05T09:28:10Z","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/2402.17886/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper considers the problem of sampling from non-logconcave distribution, based on queries of its unnormalized density. It first describes a framework, Denoising Diffusion Monte Carlo (DDMC), based on the simulation of a denoising diffusion process with its score function approximated by a generic Monte Carlo estimator. DDMC is an oracle-based meta-algorithm, where its oracle is the assumed access to samples that generate a Monte Carlo score estimator. Then we provide an implementation of this oracle, based on rejection sampling, and this turns DDMC into a true algorithm, termed Zeroth-Or","authors_text":"Kevin Rojas, Molei Tao, Ye He","cross_cats":["cs.LG","math.PR","math.ST","stat.ME","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2024-02-27T21:00:00Z","title":"Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.17886","kind":"arxiv","version":4},"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":"sha256:8fe2c8403480657b65934d9fe81f5061d7639d277f4ef9b4737cc85b4a12ed5c","target":"record","created_at":"2026-07-05T09:28:10Z","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":"9a1d7bd983671f44976bea40b69bff018498765a87e4326e3d993fa871fb8f55","cross_cats_sorted":["cs.LG","math.PR","math.ST","stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2024-02-27T21:00:00Z","title_canon_sha256":"668fb795273ff0d79e3168f3b351fc1d3bdd3ef48693ad2bc1ff92dbbc4e2a1e"},"schema_version":"1.0","source":{"id":"2402.17886","kind":"arxiv","version":4}},"canonical_sha256":"80e04bccc02e8b5a0efda8361b91ae7a3f9f1a9010cd2f549915c595aea69608","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"80e04bccc02e8b5a0efda8361b91ae7a3f9f1a9010cd2f549915c595aea69608","first_computed_at":"2026-07-05T09:28:10.984081Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:28:10.984081Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bs6fT6WiLCsr4evunEFVtluq6IiLSnpVwZl0BphVcK2pAD9Cj7srZEIrga6S49yuC+hJASvp0ltSZnbjdtGcDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:28:10.984503Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.17886","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8fe2c8403480657b65934d9fe81f5061d7639d277f4ef9b4737cc85b4a12ed5c","sha256:7b337f1615aca87afdfbc375c3b695eaa3557a1ed4d767b770fbb9513e4cfbc7"],"state_sha256":"b9b0b86d1a808b2ea2dabbf74364e5a8e6f810e0f8b380b37aa4696337a95974"}