{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:6DEYGOMKYGGCXWKIFCW5534MHQ","short_pith_number":"pith:6DEYGOMK","canonical_record":{"source":{"id":"2401.15645","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2024-01-28T12:47:39Z","cross_cats_sorted":["cs.LG","cs.NA","math.NA","physics.comp-ph","stat.ML"],"title_canon_sha256":"910d275014415ac5f4d16c2c0d663fec0bf897d821eaab80aa49d05b5ae46cbc","abstract_canon_sha256":"8834072cfafd9691c741225cbf4cdeb80da4b18ba3af18b472b198c2e9c3107c"},"schema_version":"1.0"},"canonical_sha256":"f0c983398ac18c2bd94828addeef8c3c2fe0a16106d5ffbb029110cba7e42526","source":{"kind":"arxiv","id":"2401.15645","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.15645","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"arxiv_version","alias_value":"2401.15645v2","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.15645","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_12","alias_value":"6DEYGOMKYGGC","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"6DEYGOMKYGGCXWKI","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"6DEYGOMK","created_at":"2026-07-05T09:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:6DEYGOMKYGGCXWKIFCW5534MHQ","target":"record","payload":{"canonical_record":{"source":{"id":"2401.15645","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2024-01-28T12:47:39Z","cross_cats_sorted":["cs.LG","cs.NA","math.NA","physics.comp-ph","stat.ML"],"title_canon_sha256":"910d275014415ac5f4d16c2c0d663fec0bf897d821eaab80aa49d05b5ae46cbc","abstract_canon_sha256":"8834072cfafd9691c741225cbf4cdeb80da4b18ba3af18b472b198c2e9c3107c"},"schema_version":"1.0"},"canonical_sha256":"f0c983398ac18c2bd94828addeef8c3c2fe0a16106d5ffbb029110cba7e42526","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:31:43.252433Z","signature_b64":"XencHbD2/zCtEA/U92c72X67Whh+hZBdWHFnlqxE3NxgEkmu0umTGKmtAsw8h2DVK3gPquOurWZvOXacMnxiDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f0c983398ac18c2bd94828addeef8c3c2fe0a16106d5ffbb029110cba7e42526","last_reissued_at":"2026-07-05T09:31:43.251935Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:31:43.251935Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.15645","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:31:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x0RzDw4dsyhuvV2Kaj20gR/VmjUDqIgM2gv8F1lVtAJhsW/hh0X1DfWlQehAkePZZN267fe/gMAJBqbECHRZCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:34:35.216701Z"},"content_sha256":"dcf5d59269ca0a20a7294201a87e935d6eae35440aa1dcdf80c5ec02c61f10ad","schema_version":"1.0","event_id":"sha256:dcf5d59269ca0a20a7294201a87e935d6eae35440aa1dcdf80c5ec02c61f10ad"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:6DEYGOMKYGGCXWKIFCW5534MHQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Ensemble-Based Annealed Importance Sampling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NA","math.NA","physics.comp-ph","stat.ML"],"primary_cat":"stat.CO","authors_text":"Haoxuan Chen, Lexing Ying","submitted_at":"2024-01-28T12:47:39Z","abstract_excerpt":"Sampling from a multimodal distribution is a fundamental and challenging problem in computational science and statistics. Among various approaches proposed for this task, one popular method is Annealed Importance Sampling (AIS). In this paper, we propose an ensemble-based version of AIS by combining it with population-based Monte Carlo methods to improve its efficiency. By keeping track of an ensemble instead of a single particle along some continuation path between the starting distribution and the target distribution, we take advantage of the interaction within the ensemble to encourage the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.15645","kind":"arxiv","version":2},"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/2401.15645/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:31:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+hEzMRdEinePpobl7K8PlwJ0s9D+b27hyPQhxkX9wfsAnW4U7t/Y6Ho2zWwLx/GtLUg+qNn4SG02Qy13YY+fDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:34:35.217602Z"},"content_sha256":"171a80ba3904ddb2e5bf08534e40afc6fb9a0b66067471c05a4415151ee1f36a","schema_version":"1.0","event_id":"sha256:171a80ba3904ddb2e5bf08534e40afc6fb9a0b66067471c05a4415151ee1f36a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6DEYGOMKYGGCXWKIFCW5534MHQ/bundle.json","state_url":"https://pith.science/pith/6DEYGOMKYGGCXWKIFCW5534MHQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6DEYGOMKYGGCXWKIFCW5534MHQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T16:34:35Z","links":{"resolver":"https://pith.science/pith/6DEYGOMKYGGCXWKIFCW5534MHQ","bundle":"https://pith.science/pith/6DEYGOMKYGGCXWKIFCW5534MHQ/bundle.json","state":"https://pith.science/pith/6DEYGOMKYGGCXWKIFCW5534MHQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6DEYGOMKYGGCXWKIFCW5534MHQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:6DEYGOMKYGGCXWKIFCW5534MHQ","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":"8834072cfafd9691c741225cbf4cdeb80da4b18ba3af18b472b198c2e9c3107c","cross_cats_sorted":["cs.LG","cs.NA","math.NA","physics.comp-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2024-01-28T12:47:39Z","title_canon_sha256":"910d275014415ac5f4d16c2c0d663fec0bf897d821eaab80aa49d05b5ae46cbc"},"schema_version":"1.0","source":{"id":"2401.15645","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.15645","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"arxiv_version","alias_value":"2401.15645v2","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.15645","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_12","alias_value":"6DEYGOMKYGGC","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"6DEYGOMKYGGCXWKI","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"6DEYGOMK","created_at":"2026-07-05T09:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:171a80ba3904ddb2e5bf08534e40afc6fb9a0b66067471c05a4415151ee1f36a","target":"graph","created_at":"2026-07-05T09:31:43Z","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/2401.15645/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sampling from a multimodal distribution is a fundamental and challenging problem in computational science and statistics. Among various approaches proposed for this task, one popular method is Annealed Importance Sampling (AIS). In this paper, we propose an ensemble-based version of AIS by combining it with population-based Monte Carlo methods to improve its efficiency. By keeping track of an ensemble instead of a single particle along some continuation path between the starting distribution and the target distribution, we take advantage of the interaction within the ensemble to encourage the ","authors_text":"Haoxuan Chen, Lexing Ying","cross_cats":["cs.LG","cs.NA","math.NA","physics.comp-ph","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2024-01-28T12:47:39Z","title":"Ensemble-Based Annealed Importance Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.15645","kind":"arxiv","version":2},"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:dcf5d59269ca0a20a7294201a87e935d6eae35440aa1dcdf80c5ec02c61f10ad","target":"record","created_at":"2026-07-05T09:31:43Z","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":"8834072cfafd9691c741225cbf4cdeb80da4b18ba3af18b472b198c2e9c3107c","cross_cats_sorted":["cs.LG","cs.NA","math.NA","physics.comp-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2024-01-28T12:47:39Z","title_canon_sha256":"910d275014415ac5f4d16c2c0d663fec0bf897d821eaab80aa49d05b5ae46cbc"},"schema_version":"1.0","source":{"id":"2401.15645","kind":"arxiv","version":2}},"canonical_sha256":"f0c983398ac18c2bd94828addeef8c3c2fe0a16106d5ffbb029110cba7e42526","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f0c983398ac18c2bd94828addeef8c3c2fe0a16106d5ffbb029110cba7e42526","first_computed_at":"2026-07-05T09:31:43.251935Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:31:43.251935Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XencHbD2/zCtEA/U92c72X67Whh+hZBdWHFnlqxE3NxgEkmu0umTGKmtAsw8h2DVK3gPquOurWZvOXacMnxiDA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:31:43.252433Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.15645","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dcf5d59269ca0a20a7294201a87e935d6eae35440aa1dcdf80c5ec02c61f10ad","sha256:171a80ba3904ddb2e5bf08534e40afc6fb9a0b66067471c05a4415151ee1f36a"],"state_sha256":"7f60f4f588942e1758b853a0469b4e7b7ee8ff1e2ba69d7affaa7d4f162bf6d8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RJ5wDQRHgSHa1cFlj/4cKGoRFGcmJM3Xqt8zSIfk/clLUSZ8iy/NhNkZdEU+8s2UmN3BNlnowuN1WZ4PrGRIDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T16:34:35.224618Z","bundle_sha256":"39c19f4ee8f40e4885111eb4e0c7aeca936c0f8910f45ff2ee0c0abea252b571"}}