{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:2MC5PGNJ7BOZXPFTNNVGCORH6V","short_pith_number":"pith:2MC5PGNJ","canonical_record":{"source":{"id":"2604.02094","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"math.ST","submitted_at":"2026-04-02T14:20:51Z","cross_cats_sorted":["math.PR","stat.TH"],"title_canon_sha256":"406c377dbbc235ccfe977d8e960d2203044edd33332a336ce54961e48947c134","abstract_canon_sha256":"94e5c527615c30de3d1d48ac715ae2398946f2fc5ce5fedc60834e8829d1f508"},"schema_version":"1.0"},"canonical_sha256":"d305d799a9f85d9bbcb36b6a613a27f541e7cbca4a1e731820201ddf6323b4cd","source":{"kind":"arxiv","id":"2604.02094","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.02094","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"arxiv_version","alias_value":"2604.02094v2","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.02094","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"pith_short_12","alias_value":"2MC5PGNJ7BOZ","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"pith_short_16","alias_value":"2MC5PGNJ7BOZXPFT","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"pith_short_8","alias_value":"2MC5PGNJ","created_at":"2026-05-29T02:05:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:2MC5PGNJ7BOZXPFTNNVGCORH6V","target":"record","payload":{"canonical_record":{"source":{"id":"2604.02094","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"math.ST","submitted_at":"2026-04-02T14:20:51Z","cross_cats_sorted":["math.PR","stat.TH"],"title_canon_sha256":"406c377dbbc235ccfe977d8e960d2203044edd33332a336ce54961e48947c134","abstract_canon_sha256":"94e5c527615c30de3d1d48ac715ae2398946f2fc5ce5fedc60834e8829d1f508"},"schema_version":"1.0"},"canonical_sha256":"d305d799a9f85d9bbcb36b6a613a27f541e7cbca4a1e731820201ddf6323b4cd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T02:05:44.220591Z","signature_b64":"sMskwKfLmME4vb/iIDcKSwVoD8zdp/ETmtdh0GMHIfNO6J2MykgVTfUJTqSHPSOoZSnPysjxlw71a0fpWAQGBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d305d799a9f85d9bbcb36b6a613a27f541e7cbca4a1e731820201ddf6323b4cd","last_reissued_at":"2026-05-29T02:05:44.219933Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T02:05:44.219933Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2604.02094","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":"2026-05-29T02:05:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aGi9GLdqvY94JzdDMrgSqGsS0BzSfYIZJ6ec/PxE5FhLUu0LPB2tfnRa9v4PUL9gF1kpYEOC33IJXHOxGqxbDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T06:58:14.823145Z"},"content_sha256":"cb5b0e15ad6c4e0305eb8599850f4c48865cf49de462c4f40dc962dcf5c5d075","schema_version":"1.0","event_id":"sha256:cb5b0e15ad6c4e0305eb8599850f4c48865cf49de462c4f40dc962dcf5c5d075"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:2MC5PGNJ7BOZXPFTNNVGCORH6V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Importance sampling for Bayesian inference: polynomial-dimension dependent error bounds","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["math.PR","stat.TH"],"primary_cat":"math.ST","authors_text":"Fabi\\'an Gonz\\'alez, Joaqu\\'in M\\'iguez, V\\'ictor Elvira","submitted_at":"2026-04-02T14:20:51Z","abstract_excerpt":"Many Bayesian inference problems involve high-dimensional models where the performance of standard importance sampling (IS) methods often degrades rapidly as the dimensionality increases. Classical analyses of IS typically rely on the assumption that observations are arbitrary but fixed (i.e., deterministic), thereby neglecting the probabilistic structure that the Bayesian model induces on the data. In this paper, we adopt the perspective that observations are themselves random variables whose distribution is governed by the underlying model. Within this probabilistic framework, we identify a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.02094","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/2604.02094/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":"2026-05-29T02:05:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BWETPfkO+V32uHPzeVHTY8cND5/DsFlZ8XQbSpzWSvbIMH/rYKt7BJB4u1kbAZWRMNcAlZ600VDdImnN8GaiDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T06:58:14.823536Z"},"content_sha256":"6b5dadd6c577bfd0f2484142c47b1a33d424c424fc6d151f8162356bb77243f4","schema_version":"1.0","event_id":"sha256:6b5dadd6c577bfd0f2484142c47b1a33d424c424fc6d151f8162356bb77243f4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2MC5PGNJ7BOZXPFTNNVGCORH6V/bundle.json","state_url":"https://pith.science/pith/2MC5PGNJ7BOZXPFTNNVGCORH6V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2MC5PGNJ7BOZXPFTNNVGCORH6V/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":"2026-06-27T06:58:14Z","links":{"resolver":"https://pith.science/pith/2MC5PGNJ7BOZXPFTNNVGCORH6V","bundle":"https://pith.science/pith/2MC5PGNJ7BOZXPFTNNVGCORH6V/bundle.json","state":"https://pith.science/pith/2MC5PGNJ7BOZXPFTNNVGCORH6V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2MC5PGNJ7BOZXPFTNNVGCORH6V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:2MC5PGNJ7BOZXPFTNNVGCORH6V","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":"94e5c527615c30de3d1d48ac715ae2398946f2fc5ce5fedc60834e8829d1f508","cross_cats_sorted":["math.PR","stat.TH"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"math.ST","submitted_at":"2026-04-02T14:20:51Z","title_canon_sha256":"406c377dbbc235ccfe977d8e960d2203044edd33332a336ce54961e48947c134"},"schema_version":"1.0","source":{"id":"2604.02094","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.02094","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"arxiv_version","alias_value":"2604.02094v2","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.02094","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"pith_short_12","alias_value":"2MC5PGNJ7BOZ","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"pith_short_16","alias_value":"2MC5PGNJ7BOZXPFT","created_at":"2026-05-29T02:05:44Z"},{"alias_kind":"pith_short_8","alias_value":"2MC5PGNJ","created_at":"2026-05-29T02:05:44Z"}],"graph_snapshots":[{"event_id":"sha256:6b5dadd6c577bfd0f2484142c47b1a33d424c424fc6d151f8162356bb77243f4","target":"graph","created_at":"2026-05-29T02:05:44Z","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/2604.02094/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Many Bayesian inference problems involve high-dimensional models where the performance of standard importance sampling (IS) methods often degrades rapidly as the dimensionality increases. Classical analyses of IS typically rely on the assumption that observations are arbitrary but fixed (i.e., deterministic), thereby neglecting the probabilistic structure that the Bayesian model induces on the data. In this paper, we adopt the perspective that observations are themselves random variables whose distribution is governed by the underlying model. Within this probabilistic framework, we identify a ","authors_text":"Fabi\\'an Gonz\\'alez, Joaqu\\'in M\\'iguez, V\\'ictor Elvira","cross_cats":["math.PR","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"math.ST","submitted_at":"2026-04-02T14:20:51Z","title":"Importance sampling for Bayesian inference: polynomial-dimension dependent error bounds"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.02094","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:cb5b0e15ad6c4e0305eb8599850f4c48865cf49de462c4f40dc962dcf5c5d075","target":"record","created_at":"2026-05-29T02:05:44Z","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":"94e5c527615c30de3d1d48ac715ae2398946f2fc5ce5fedc60834e8829d1f508","cross_cats_sorted":["math.PR","stat.TH"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"math.ST","submitted_at":"2026-04-02T14:20:51Z","title_canon_sha256":"406c377dbbc235ccfe977d8e960d2203044edd33332a336ce54961e48947c134"},"schema_version":"1.0","source":{"id":"2604.02094","kind":"arxiv","version":2}},"canonical_sha256":"d305d799a9f85d9bbcb36b6a613a27f541e7cbca4a1e731820201ddf6323b4cd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d305d799a9f85d9bbcb36b6a613a27f541e7cbca4a1e731820201ddf6323b4cd","first_computed_at":"2026-05-29T02:05:44.219933Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T02:05:44.219933Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sMskwKfLmME4vb/iIDcKSwVoD8zdp/ETmtdh0GMHIfNO6J2MykgVTfUJTqSHPSOoZSnPysjxlw71a0fpWAQGBQ==","signature_status":"signed_v1","signed_at":"2026-05-29T02:05:44.220591Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.02094","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cb5b0e15ad6c4e0305eb8599850f4c48865cf49de462c4f40dc962dcf5c5d075","sha256:6b5dadd6c577bfd0f2484142c47b1a33d424c424fc6d151f8162356bb77243f4"],"state_sha256":"206a81897076f244ecb6a1b045d8d972555f4f1f3272f3d58f10f43d11f7579e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KkIljGFaZleKSRpByIgJTpcvdCA5pAHE7en+GN8qB8NR2pVoTz6PtrJJkPyBsu5pZPHBGGTx499vuTl/8ISMCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T06:58:14.825440Z","bundle_sha256":"19c72d568bb037f9b346d6e8e41814618d514282445583d9741776c0a851979a"}}