{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:BXCZ7TDM6YUWBQTQQARQYZLFZS","short_pith_number":"pith:BXCZ7TDM","schema_version":"1.0","canonical_sha256":"0dc59fcc6cf62960c27080230c6565cc8e8d9fc141f5ddc6fb69d71750e3c258","source":{"kind":"arxiv","id":"2506.11456","version":2},"attestation_state":"computed","paper":{"title":"Fast Bayesian Optimization of Function Networks with Partial Evaluations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Peter I. Frazier, Poompol Buathong","submitted_at":"2025-06-13T04:20:36Z","abstract_excerpt":"Bayesian optimization of function networks (BOFN) is a framework for optimizing expensive-to-evaluate objective functions structured as networks, where some nodes' outputs serve as inputs for others. Many real-world applications, such as manufacturing and drug discovery, involve function networks with additional properties - nodes that can be evaluated independently and incur varying costs. A recent BOFN variant, p-KGFN, leverages this structure and enables cost-aware partial evaluations, selectively querying only a subset of nodes at each iteration. p-KGFN reduces the number of expensive obje"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.11456","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2025-06-13T04:20:36Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9b7cb7ff32888f18fe4bee81c49e110aa89e2f5e8b8de72989834da37968b17e","abstract_canon_sha256":"6c923406d798a0f2de4c39bbdb4402f4e36f9b513e08a3e87c8c77f06981766c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:25:45.939618Z","signature_b64":"qM3klh06YMN1sUYYV4RsYXcVdV5T/V2whMRvcqi8NexyIsJPLT9FzWzT9FC4AGHWakS1y+3Xuawwt7J3y2H3AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0dc59fcc6cf62960c27080230c6565cc8e8d9fc141f5ddc6fb69d71750e3c258","last_reissued_at":"2026-07-05T11:25:45.939139Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:25:45.939139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fast Bayesian Optimization of Function Networks with Partial Evaluations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Peter I. Frazier, Poompol Buathong","submitted_at":"2025-06-13T04:20:36Z","abstract_excerpt":"Bayesian optimization of function networks (BOFN) is a framework for optimizing expensive-to-evaluate objective functions structured as networks, where some nodes' outputs serve as inputs for others. Many real-world applications, such as manufacturing and drug discovery, involve function networks with additional properties - nodes that can be evaluated independently and incur varying costs. A recent BOFN variant, p-KGFN, leverages this structure and enables cost-aware partial evaluations, selectively querying only a subset of nodes at each iteration. p-KGFN reduces the number of expensive obje"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.11456","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/2506.11456/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.11456","created_at":"2026-07-05T11:25:45.939196+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.11456v2","created_at":"2026-07-05T11:25:45.939196+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.11456","created_at":"2026-07-05T11:25:45.939196+00:00"},{"alias_kind":"pith_short_12","alias_value":"BXCZ7TDM6YUW","created_at":"2026-07-05T11:25:45.939196+00:00"},{"alias_kind":"pith_short_16","alias_value":"BXCZ7TDM6YUWBQTQ","created_at":"2026-07-05T11:25:45.939196+00:00"},{"alias_kind":"pith_short_8","alias_value":"BXCZ7TDM","created_at":"2026-07-05T11:25:45.939196+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BXCZ7TDM6YUWBQTQQARQYZLFZS","json":"https://pith.science/pith/BXCZ7TDM6YUWBQTQQARQYZLFZS.json","graph_json":"https://pith.science/api/pith-number/BXCZ7TDM6YUWBQTQQARQYZLFZS/graph.json","events_json":"https://pith.science/api/pith-number/BXCZ7TDM6YUWBQTQQARQYZLFZS/events.json","paper":"https://pith.science/paper/BXCZ7TDM"},"agent_actions":{"view_html":"https://pith.science/pith/BXCZ7TDM6YUWBQTQQARQYZLFZS","download_json":"https://pith.science/pith/BXCZ7TDM6YUWBQTQQARQYZLFZS.json","view_paper":"https://pith.science/paper/BXCZ7TDM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.11456&json=true","fetch_graph":"https://pith.science/api/pith-number/BXCZ7TDM6YUWBQTQQARQYZLFZS/graph.json","fetch_events":"https://pith.science/api/pith-number/BXCZ7TDM6YUWBQTQQARQYZLFZS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BXCZ7TDM6YUWBQTQQARQYZLFZS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BXCZ7TDM6YUWBQTQQARQYZLFZS/action/storage_attestation","attest_author":"https://pith.science/pith/BXCZ7TDM6YUWBQTQQARQYZLFZS/action/author_attestation","sign_citation":"https://pith.science/pith/BXCZ7TDM6YUWBQTQQARQYZLFZS/action/citation_signature","submit_replication":"https://pith.science/pith/BXCZ7TDM6YUWBQTQQARQYZLFZS/action/replication_record"}},"created_at":"2026-07-05T11:25:45.939196+00:00","updated_at":"2026-07-05T11:25:45.939196+00:00"}