{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:YGHE3Q6VGB7JIVZXE5JEUJ4HJE","short_pith_number":"pith:YGHE3Q6V","canonical_record":{"source":{"id":"1609.02700","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-09T08:42:12Z","cross_cats_sorted":["stat.AP","stat.ME"],"title_canon_sha256":"544116888e3f68b365ffe0614e943d1a48b43a01737c0a776f2215b9fd2d29d2","abstract_canon_sha256":"e6e70c555a1704eef68625bf6578024ed2e9ba44ee0ca0902f224f7599712225"},"schema_version":"1.0"},"canonical_sha256":"c18e4dc3d5307e94573727524a27874929ded90d49f0d5914b374245fe496a0b","source":{"kind":"arxiv","id":"1609.02700","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.02700","created_at":"2026-05-18T01:04:51Z"},{"alias_kind":"arxiv_version","alias_value":"1609.02700v1","created_at":"2026-05-18T01:04:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.02700","created_at":"2026-05-18T01:04:51Z"},{"alias_kind":"pith_short_12","alias_value":"YGHE3Q6VGB7J","created_at":"2026-05-18T12:30:53Z"},{"alias_kind":"pith_short_16","alias_value":"YGHE3Q6VGB7JIVZX","created_at":"2026-05-18T12:30:53Z"},{"alias_kind":"pith_short_8","alias_value":"YGHE3Q6V","created_at":"2026-05-18T12:30:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:YGHE3Q6VGB7JIVZXE5JEUJ4HJE","target":"record","payload":{"canonical_record":{"source":{"id":"1609.02700","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-09T08:42:12Z","cross_cats_sorted":["stat.AP","stat.ME"],"title_canon_sha256":"544116888e3f68b365ffe0614e943d1a48b43a01737c0a776f2215b9fd2d29d2","abstract_canon_sha256":"e6e70c555a1704eef68625bf6578024ed2e9ba44ee0ca0902f224f7599712225"},"schema_version":"1.0"},"canonical_sha256":"c18e4dc3d5307e94573727524a27874929ded90d49f0d5914b374245fe496a0b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:04:51.478152Z","signature_b64":"oP/1fgWQx5JZMxiITY0Zx2Fd9/aWTMzVGqv415HC3v/cqt1GRulYnD9Dk3od7QFlIwQqA4T7iUgruGS6CtwrDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c18e4dc3d5307e94573727524a27874929ded90d49f0d5914b374245fe496a0b","last_reissued_at":"2026-05-18T01:04:51.477720Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:04:51.477720Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1609.02700","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":"2026-05-18T01:04:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1ZbSH61ME6rTM23FANi/PgcerWPLgnm7HeeRW8REVhybGfIHEynCepnOGjKqQmITRpKzPlcyEOhq1uZTgr6IDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T19:14:43.529776Z"},"content_sha256":"d326dbcea307fdaf2a2ee20ad4401a7dedcdd5038baa5df06ca08cc9201ebb0b","schema_version":"1.0","event_id":"sha256:d326dbcea307fdaf2a2ee20ad4401a7dedcdd5038baa5df06ca08cc9201ebb0b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:YGHE3Q6VGB7JIVZXE5JEUJ4HJE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient batch-sequential Bayesian optimization with moments of truncated Gaussian vectors","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP","stat.ME"],"primary_cat":"stat.ML","authors_text":"Cl\\'ement Chevalier, David Ginsbourger (IMSV), I2M), S\\'ebastien Marmin (IMSV","submitted_at":"2016-09-09T08:42:12Z","abstract_excerpt":"We deal with the efficient parallelization of Bayesian global optimization algorithms, and more specifically of those based on the expected improvement criterion and its variants. A closed form formula relying on multivariate Gaussian cumulative distribution functions is established for a generalized version of the multipoint expected improvement criterion. In turn, the latter relies on intermediate results that could be of independent interest concerning moments of truncated Gaussian vectors. The obtained expansion of the criterion enables studying its differentiability with respect to point "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.02700","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":"2026-05-18T01:04:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j0ZKwbeZ4f4zXDytTRbJmfl4sm6TCMjmaaUbW4t8PxOTVDJVNAm994EJIb3Baa4ed2SJcW21fpzn2OBPuHkxCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T19:14:43.530119Z"},"content_sha256":"78706bef3c3851c6265548aff8f7cb11d0a744aa37e1e0e9f1f1064201e8c2ba","schema_version":"1.0","event_id":"sha256:78706bef3c3851c6265548aff8f7cb11d0a744aa37e1e0e9f1f1064201e8c2ba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YGHE3Q6VGB7JIVZXE5JEUJ4HJE/bundle.json","state_url":"https://pith.science/pith/YGHE3Q6VGB7JIVZXE5JEUJ4HJE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YGHE3Q6VGB7JIVZXE5JEUJ4HJE/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":"2026-06-25T19:14:43Z","links":{"resolver":"https://pith.science/pith/YGHE3Q6VGB7JIVZXE5JEUJ4HJE","bundle":"https://pith.science/pith/YGHE3Q6VGB7JIVZXE5JEUJ4HJE/bundle.json","state":"https://pith.science/pith/YGHE3Q6VGB7JIVZXE5JEUJ4HJE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YGHE3Q6VGB7JIVZXE5JEUJ4HJE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:YGHE3Q6VGB7JIVZXE5JEUJ4HJE","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":"e6e70c555a1704eef68625bf6578024ed2e9ba44ee0ca0902f224f7599712225","cross_cats_sorted":["stat.AP","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-09T08:42:12Z","title_canon_sha256":"544116888e3f68b365ffe0614e943d1a48b43a01737c0a776f2215b9fd2d29d2"},"schema_version":"1.0","source":{"id":"1609.02700","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.02700","created_at":"2026-05-18T01:04:51Z"},{"alias_kind":"arxiv_version","alias_value":"1609.02700v1","created_at":"2026-05-18T01:04:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.02700","created_at":"2026-05-18T01:04:51Z"},{"alias_kind":"pith_short_12","alias_value":"YGHE3Q6VGB7J","created_at":"2026-05-18T12:30:53Z"},{"alias_kind":"pith_short_16","alias_value":"YGHE3Q6VGB7JIVZX","created_at":"2026-05-18T12:30:53Z"},{"alias_kind":"pith_short_8","alias_value":"YGHE3Q6V","created_at":"2026-05-18T12:30:53Z"}],"graph_snapshots":[{"event_id":"sha256:78706bef3c3851c6265548aff8f7cb11d0a744aa37e1e0e9f1f1064201e8c2ba","target":"graph","created_at":"2026-05-18T01:04:51Z","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":"We deal with the efficient parallelization of Bayesian global optimization algorithms, and more specifically of those based on the expected improvement criterion and its variants. A closed form formula relying on multivariate Gaussian cumulative distribution functions is established for a generalized version of the multipoint expected improvement criterion. In turn, the latter relies on intermediate results that could be of independent interest concerning moments of truncated Gaussian vectors. The obtained expansion of the criterion enables studying its differentiability with respect to point ","authors_text":"Cl\\'ement Chevalier, David Ginsbourger (IMSV), I2M), S\\'ebastien Marmin (IMSV","cross_cats":["stat.AP","stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-09T08:42:12Z","title":"Efficient batch-sequential Bayesian optimization with moments of truncated Gaussian vectors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.02700","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:d326dbcea307fdaf2a2ee20ad4401a7dedcdd5038baa5df06ca08cc9201ebb0b","target":"record","created_at":"2026-05-18T01:04:51Z","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":"e6e70c555a1704eef68625bf6578024ed2e9ba44ee0ca0902f224f7599712225","cross_cats_sorted":["stat.AP","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-09T08:42:12Z","title_canon_sha256":"544116888e3f68b365ffe0614e943d1a48b43a01737c0a776f2215b9fd2d29d2"},"schema_version":"1.0","source":{"id":"1609.02700","kind":"arxiv","version":1}},"canonical_sha256":"c18e4dc3d5307e94573727524a27874929ded90d49f0d5914b374245fe496a0b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c18e4dc3d5307e94573727524a27874929ded90d49f0d5914b374245fe496a0b","first_computed_at":"2026-05-18T01:04:51.477720Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:04:51.477720Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oP/1fgWQx5JZMxiITY0Zx2Fd9/aWTMzVGqv415HC3v/cqt1GRulYnD9Dk3od7QFlIwQqA4T7iUgruGS6CtwrDw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:04:51.478152Z","signed_message":"canonical_sha256_bytes"},"source_id":"1609.02700","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d326dbcea307fdaf2a2ee20ad4401a7dedcdd5038baa5df06ca08cc9201ebb0b","sha256:78706bef3c3851c6265548aff8f7cb11d0a744aa37e1e0e9f1f1064201e8c2ba"],"state_sha256":"572a502ad95eb88b377c7cb89cac6362bff0e1cdb28b95cbbfdef73ffeb9d291"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XyWqFloscatcuqFqr3yAQyhLwjhRI1fmSoPzoCjPfshSkQnYcTZFrlxzFq3jhToUbk3fOJ1gOuSijUL2TkFLCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T19:14:43.532086Z","bundle_sha256":"80c03146c411593eab68c1bfb556ac98c760eb7cda2a2e3ce3ce99df0d550587"}}