{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:AP4MXXNGFEZDECVKNK4V6BEM47","short_pith_number":"pith:AP4MXXNG","canonical_record":{"source":{"id":"2306.01095","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-01T19:10:57Z","cross_cats_sorted":["cs.AI","cs.CE"],"title_canon_sha256":"8967a57ec0abf870519ba7209c475bdc2e148310deb3d854ed0447ce2769c366","abstract_canon_sha256":"07cfe544e4a8a48ec615ad52839e77fdb95d888556477551805706307b64f6f2"},"schema_version":"1.0"},"canonical_sha256":"03f8cbdda62932320aaa6ab95f048ce7fcbae4912a2757b3cb16098798a0d0d0","source":{"kind":"arxiv","id":"2306.01095","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.01095","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"arxiv_version","alias_value":"2306.01095v4","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.01095","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"pith_short_12","alias_value":"AP4MXXNGFEZD","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"pith_short_16","alias_value":"AP4MXXNGFEZDECVK","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"pith_short_8","alias_value":"AP4MXXNG","created_at":"2026-07-05T09:03:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:AP4MXXNGFEZDECVKNK4V6BEM47","target":"record","payload":{"canonical_record":{"source":{"id":"2306.01095","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-01T19:10:57Z","cross_cats_sorted":["cs.AI","cs.CE"],"title_canon_sha256":"8967a57ec0abf870519ba7209c475bdc2e148310deb3d854ed0447ce2769c366","abstract_canon_sha256":"07cfe544e4a8a48ec615ad52839e77fdb95d888556477551805706307b64f6f2"},"schema_version":"1.0"},"canonical_sha256":"03f8cbdda62932320aaa6ab95f048ce7fcbae4912a2757b3cb16098798a0d0d0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:03:39.628946Z","signature_b64":"7i0y25WG/Rw3ieIluyTFsDxkf2wkwI8UNadzx6Qpk+rvH6dOwEzWAA3pAl1D/tZeH2tee6nBl85pcxjz7erIAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"03f8cbdda62932320aaa6ab95f048ce7fcbae4912a2757b3cb16098798a0d0d0","last_reissued_at":"2026-07-05T09:03:39.628357Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:03:39.628357Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.01095","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:03:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"87RbAu842gRtB2ZHlvzNtZOGfVeyF7Sa52R7DkbGnw0PSAMtV+rgYkg5IqooJpBxxaGKn7S/+8eMsb+/DAgnBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T20:26:28.529271Z"},"content_sha256":"5df3f6747b86ed3014c81f1a1308d97c00540efec1f19911fc81322a8f49d772","schema_version":"1.0","event_id":"sha256:5df3f6747b86ed3014c81f1a1308d97c00540efec1f19911fc81322a8f49d772"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:AP4MXXNGFEZDECVKNK4V6BEM47","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CE"],"primary_cat":"cs.LG","authors_text":"Alireza Javanmardi, Eyke H\\\"ullermeier, Hans-Peter Seidel, Navid Ansari, Vahid Babaei","submitted_at":"2023-06-01T19:10:57Z","abstract_excerpt":"Bayesian optimization (BO) provides a powerful framework for optimizing black-box, expensive-to-evaluate functions. It is therefore an attractive tool for engineering design problems, typically involving multiple objectives. Thanks to the rapid advances in fabrication and measurement methods as well as parallel computing infrastructure, querying many design problems can be heavily parallelized. This class of problems challenges BO with an unprecedented setup where it has to deal with very large batches, shifting its focus from sample efficiency to iteration efficiency. We present a novel Bayes"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.01095","kind":"arxiv","version":4},"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/2306.01095/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":"2026-07-05T09:03:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rbmWdLgdHtp/Idn4SAEJWEHkz5+NEqLAsL3f/ZFGT2FfTywFp6HclhY6aIOojhVWW0SJRxyoygfevWmiOg1HDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T20:26:28.530060Z"},"content_sha256":"364fc9022d85926da48d9c7f046dcef9f321092cf1afeab46bb67a259fa63ee2","schema_version":"1.0","event_id":"sha256:364fc9022d85926da48d9c7f046dcef9f321092cf1afeab46bb67a259fa63ee2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AP4MXXNGFEZDECVKNK4V6BEM47/bundle.json","state_url":"https://pith.science/pith/AP4MXXNGFEZDECVKNK4V6BEM47/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AP4MXXNGFEZDECVKNK4V6BEM47/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":"2026-08-12T20:26:28Z","links":{"resolver":"https://pith.science/pith/AP4MXXNGFEZDECVKNK4V6BEM47","bundle":"https://pith.science/pith/AP4MXXNGFEZDECVKNK4V6BEM47/bundle.json","state":"https://pith.science/pith/AP4MXXNGFEZDECVKNK4V6BEM47/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AP4MXXNGFEZDECVKNK4V6BEM47/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:AP4MXXNGFEZDECVKNK4V6BEM47","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":"07cfe544e4a8a48ec615ad52839e77fdb95d888556477551805706307b64f6f2","cross_cats_sorted":["cs.AI","cs.CE"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-01T19:10:57Z","title_canon_sha256":"8967a57ec0abf870519ba7209c475bdc2e148310deb3d854ed0447ce2769c366"},"schema_version":"1.0","source":{"id":"2306.01095","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.01095","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"arxiv_version","alias_value":"2306.01095v4","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.01095","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"pith_short_12","alias_value":"AP4MXXNGFEZD","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"pith_short_16","alias_value":"AP4MXXNGFEZDECVK","created_at":"2026-07-05T09:03:39Z"},{"alias_kind":"pith_short_8","alias_value":"AP4MXXNG","created_at":"2026-07-05T09:03:39Z"}],"graph_snapshots":[{"event_id":"sha256:364fc9022d85926da48d9c7f046dcef9f321092cf1afeab46bb67a259fa63ee2","target":"graph","created_at":"2026-07-05T09:03:39Z","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/2306.01095/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Bayesian optimization (BO) provides a powerful framework for optimizing black-box, expensive-to-evaluate functions. It is therefore an attractive tool for engineering design problems, typically involving multiple objectives. Thanks to the rapid advances in fabrication and measurement methods as well as parallel computing infrastructure, querying many design problems can be heavily parallelized. This class of problems challenges BO with an unprecedented setup where it has to deal with very large batches, shifting its focus from sample efficiency to iteration efficiency. We present a novel Bayes","authors_text":"Alireza Javanmardi, Eyke H\\\"ullermeier, Hans-Peter Seidel, Navid Ansari, Vahid Babaei","cross_cats":["cs.AI","cs.CE"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-01T19:10:57Z","title":"Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.01095","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":"sha256:5df3f6747b86ed3014c81f1a1308d97c00540efec1f19911fc81322a8f49d772","target":"record","created_at":"2026-07-05T09:03:39Z","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":"07cfe544e4a8a48ec615ad52839e77fdb95d888556477551805706307b64f6f2","cross_cats_sorted":["cs.AI","cs.CE"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-06-01T19:10:57Z","title_canon_sha256":"8967a57ec0abf870519ba7209c475bdc2e148310deb3d854ed0447ce2769c366"},"schema_version":"1.0","source":{"id":"2306.01095","kind":"arxiv","version":4}},"canonical_sha256":"03f8cbdda62932320aaa6ab95f048ce7fcbae4912a2757b3cb16098798a0d0d0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"03f8cbdda62932320aaa6ab95f048ce7fcbae4912a2757b3cb16098798a0d0d0","first_computed_at":"2026-07-05T09:03:39.628357Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:03:39.628357Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7i0y25WG/Rw3ieIluyTFsDxkf2wkwI8UNadzx6Qpk+rvH6dOwEzWAA3pAl1D/tZeH2tee6nBl85pcxjz7erIAg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:03:39.628946Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.01095","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5df3f6747b86ed3014c81f1a1308d97c00540efec1f19911fc81322a8f49d772","sha256:364fc9022d85926da48d9c7f046dcef9f321092cf1afeab46bb67a259fa63ee2"],"state_sha256":"bf1b6ab5fecd674e9af2dbb7f5e36d2af98dc8b8cecccb1452d456c685571377"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W/SQKThM4/7n9Uz3Xd3QauRPEXuOr6xTLcqPc5pyoq5yJTQ1pnPYvn4Vy2lxwPefF4iTLkzgn4nQzQ8MgEI4Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T20:26:28.540593Z","bundle_sha256":"0afb7e44f7277021130545a4073fbda27c908caac5f2c98423c5d2c8d40d7787"}}