{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:T5QMOT5QF46DQS2NNVWIY2F5CX","short_pith_number":"pith:T5QMOT5Q","canonical_record":{"source":{"id":"1512.00205","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-12-01T10:16:46Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"f0b1a921dac3b0faf8cc7d0ecc85a6b0ee01d96ea579d46926b517753d0a82cd","abstract_canon_sha256":"2b8e816c3f017df310a4828e1c8968f306e9cc6b821c986acfb19a9de4a06e5d"},"schema_version":"1.0"},"canonical_sha256":"9f60c74fb02f3c384b4d6d6c8c68bd15e2c58816cc57eabbca5d66c5d3c46eb9","source":{"kind":"arxiv","id":"1512.00205","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.00205","created_at":"2026-05-18T01:25:32Z"},{"alias_kind":"arxiv_version","alias_value":"1512.00205v1","created_at":"2026-05-18T01:25:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.00205","created_at":"2026-05-18T01:25:32Z"},{"alias_kind":"pith_short_12","alias_value":"T5QMOT5QF46D","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"T5QMOT5QF46DQS2N","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"T5QMOT5Q","created_at":"2026-05-18T12:29:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:T5QMOT5QF46DQS2NNVWIY2F5CX","target":"record","payload":{"canonical_record":{"source":{"id":"1512.00205","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-12-01T10:16:46Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"f0b1a921dac3b0faf8cc7d0ecc85a6b0ee01d96ea579d46926b517753d0a82cd","abstract_canon_sha256":"2b8e816c3f017df310a4828e1c8968f306e9cc6b821c986acfb19a9de4a06e5d"},"schema_version":"1.0"},"canonical_sha256":"9f60c74fb02f3c384b4d6d6c8c68bd15e2c58816cc57eabbca5d66c5d3c46eb9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:25:32.465598Z","signature_b64":"a0efGaLnS2UZy61AhYFlHYPLDG4TLGv+n7LuVGbTbLAWefgeJrlSKKs7JvqldwXYo3fQGXrw3DepXfRcOccQDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9f60c74fb02f3c384b4d6d6c8c68bd15e2c58816cc57eabbca5d66c5d3c46eb9","last_reissued_at":"2026-05-18T01:25:32.464919Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:25:32.464919Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1512.00205","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:25:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yyBkAqsazE5pwbUxIskbcNM2JgSnICrCRDNMXXXgL4uey+OIOOgySvoyLR1nV2NwAbHJwMFF+4bQ0B8DYpBZBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T17:40:29.854756Z"},"content_sha256":"638492629bf7bca89d50ec82b3ec36e96d85b442301f1e582fe34da4eb114c2e","schema_version":"1.0","event_id":"sha256:638492629bf7bca89d50ec82b3ec36e96d85b442301f1e582fe34da4eb114c2e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:T5QMOT5QF46DQS2NNVWIY2F5CX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Divide and conquer in ABC: Expectation-Progagation algorithms for likelihood-free inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.CO","authors_text":"Nicolas Chopin, Simon Barthelm\\'e, Vincent Cottet","submitted_at":"2015-12-01T10:16:46Z","abstract_excerpt":"ABC algorithms are notoriously expensive in computing time, as they require simulating many complete artificial datasets from the model. We advocate in this paper a \"divide and conquer\" approach to ABC, where we split the likelihood into n factors, and combine in some way n \"local\" ABC approximations of each factor. This has two advantages: (a) such an approach is typically much faster than standard ABC and (b) it makes it possible to use local summary statistics (i.e. summary statistics that depend only on the data-points that correspond to a single factor), rather than global summary statist"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.00205","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:25:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YJiwWSbYIjex9zIFaaq+VFCFShwr5Hyq4nQDRxVld5ynn4HpOGVXRpqKPm5xtAVa3oFFe900rR9DoTzDhsm1AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T17:40:29.855098Z"},"content_sha256":"f183e6801a2716d12c6407e169a6684536fa46c3ae84c9076df8e2003327a64d","schema_version":"1.0","event_id":"sha256:f183e6801a2716d12c6407e169a6684536fa46c3ae84c9076df8e2003327a64d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/T5QMOT5QF46DQS2NNVWIY2F5CX/bundle.json","state_url":"https://pith.science/pith/T5QMOT5QF46DQS2NNVWIY2F5CX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/T5QMOT5QF46DQS2NNVWIY2F5CX/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":"2026-06-03T17:40:29Z","links":{"resolver":"https://pith.science/pith/T5QMOT5QF46DQS2NNVWIY2F5CX","bundle":"https://pith.science/pith/T5QMOT5QF46DQS2NNVWIY2F5CX/bundle.json","state":"https://pith.science/pith/T5QMOT5QF46DQS2NNVWIY2F5CX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/T5QMOT5QF46DQS2NNVWIY2F5CX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:T5QMOT5QF46DQS2NNVWIY2F5CX","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":"2b8e816c3f017df310a4828e1c8968f306e9cc6b821c986acfb19a9de4a06e5d","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-12-01T10:16:46Z","title_canon_sha256":"f0b1a921dac3b0faf8cc7d0ecc85a6b0ee01d96ea579d46926b517753d0a82cd"},"schema_version":"1.0","source":{"id":"1512.00205","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.00205","created_at":"2026-05-18T01:25:32Z"},{"alias_kind":"arxiv_version","alias_value":"1512.00205v1","created_at":"2026-05-18T01:25:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.00205","created_at":"2026-05-18T01:25:32Z"},{"alias_kind":"pith_short_12","alias_value":"T5QMOT5QF46D","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"T5QMOT5QF46DQS2N","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"T5QMOT5Q","created_at":"2026-05-18T12:29:42Z"}],"graph_snapshots":[{"event_id":"sha256:f183e6801a2716d12c6407e169a6684536fa46c3ae84c9076df8e2003327a64d","target":"graph","created_at":"2026-05-18T01:25:32Z","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"},"paper":{"abstract_excerpt":"ABC algorithms are notoriously expensive in computing time, as they require simulating many complete artificial datasets from the model. We advocate in this paper a \"divide and conquer\" approach to ABC, where we split the likelihood into n factors, and combine in some way n \"local\" ABC approximations of each factor. This has two advantages: (a) such an approach is typically much faster than standard ABC and (b) it makes it possible to use local summary statistics (i.e. summary statistics that depend only on the data-points that correspond to a single factor), rather than global summary statist","authors_text":"Nicolas Chopin, Simon Barthelm\\'e, Vincent Cottet","cross_cats":["stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-12-01T10:16:46Z","title":"Divide and conquer in ABC: Expectation-Progagation algorithms for likelihood-free inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.00205","kind":"arxiv","version":1},"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":"sha256:638492629bf7bca89d50ec82b3ec36e96d85b442301f1e582fe34da4eb114c2e","target":"record","created_at":"2026-05-18T01:25:32Z","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":"2b8e816c3f017df310a4828e1c8968f306e9cc6b821c986acfb19a9de4a06e5d","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-12-01T10:16:46Z","title_canon_sha256":"f0b1a921dac3b0faf8cc7d0ecc85a6b0ee01d96ea579d46926b517753d0a82cd"},"schema_version":"1.0","source":{"id":"1512.00205","kind":"arxiv","version":1}},"canonical_sha256":"9f60c74fb02f3c384b4d6d6c8c68bd15e2c58816cc57eabbca5d66c5d3c46eb9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9f60c74fb02f3c384b4d6d6c8c68bd15e2c58816cc57eabbca5d66c5d3c46eb9","first_computed_at":"2026-05-18T01:25:32.464919Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:25:32.464919Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"a0efGaLnS2UZy61AhYFlHYPLDG4TLGv+n7LuVGbTbLAWefgeJrlSKKs7JvqldwXYo3fQGXrw3DepXfRcOccQDw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:25:32.465598Z","signed_message":"canonical_sha256_bytes"},"source_id":"1512.00205","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:638492629bf7bca89d50ec82b3ec36e96d85b442301f1e582fe34da4eb114c2e","sha256:f183e6801a2716d12c6407e169a6684536fa46c3ae84c9076df8e2003327a64d"],"state_sha256":"020e7c9c4360098dd90d344575395bc3a19706c294f22a3f3bd2b2b39e42f2bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aRDtcGz9NDnWLOzqaNuVWXzNGc9xNARuVzCXmimd7ZvbwxdOHD67fQvJnBuEkDH08z8M5hLQU1ZyaANJtXUHAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T17:40:29.857008Z","bundle_sha256":"cc7345537852c5b31ceea95d43621989d9d4b9fb09d3dd5be314abec7caff750"}}