{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:YH3EIYYUDGAKP6GKQ5OY7VNSSI","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":"a1f49935353e242e926f0a999bf093ecb2c41fbc051407757855325eda0feae0","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-08-14T21:40:13Z","title_canon_sha256":"07f53dc97e2ee95ba3a62d1baf20fd32cbd15224fc9f37d89fd4f50fb6947c1f"},"schema_version":"1.0","source":{"id":"1908.05357","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.05357","created_at":"2026-07-04T23:56:50Z"},{"alias_kind":"arxiv_version","alias_value":"1908.05357v1","created_at":"2026-07-04T23:56:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.05357","created_at":"2026-07-04T23:56:50Z"},{"alias_kind":"pith_short_12","alias_value":"YH3EIYYUDGAK","created_at":"2026-07-04T23:56:50Z"},{"alias_kind":"pith_short_16","alias_value":"YH3EIYYUDGAKP6GK","created_at":"2026-07-04T23:56:50Z"},{"alias_kind":"pith_short_8","alias_value":"YH3EIYYU","created_at":"2026-07-04T23:56:50Z"}],"graph_snapshots":[{"event_id":"sha256:050ca1a064f44bc5ffb262fb5379fbd385f5004b81d61360f986e9e124ba7331","target":"graph","created_at":"2026-07-04T23:56:50Z","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/1908.05357/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A computer code can simulate a system's propagation of variation from random inputs to output measures of quality. Our aim here is to estimate a critical output tail probability or quantile without a large Monte Carlo experiment. Instead, we build a statistical surrogate for the input-output relationship with a modest number of evaluations and then sequentially add further runs, guided by a criterion to improve the estimate. We compare two criteria in the literature. Moreover, we investigate two practical questions: how to design the initial code runs and how to model the input distribution. H","authors_text":"Hao Chen, William J. Welch","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-08-14T21:40:13Z","title":"Sequential Computer Experimental Design for Estimating an Extreme Probability or Quantile"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.05357","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":"sha256:3e38c3c91daf9b07d34532d3007d905d7696817f834a2f800e8e03fff8bc3370","target":"record","created_at":"2026-07-04T23:56:50Z","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":"a1f49935353e242e926f0a999bf093ecb2c41fbc051407757855325eda0feae0","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-08-14T21:40:13Z","title_canon_sha256":"07f53dc97e2ee95ba3a62d1baf20fd32cbd15224fc9f37d89fd4f50fb6947c1f"},"schema_version":"1.0","source":{"id":"1908.05357","kind":"arxiv","version":1}},"canonical_sha256":"c1f64463141980a7f8ca875d8fd5b2922626dbe2a9a001ad4386e5caba2d5785","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c1f64463141980a7f8ca875d8fd5b2922626dbe2a9a001ad4386e5caba2d5785","first_computed_at":"2026-07-04T23:56:50.827523Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:56:50.827523Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5Q2hi7+jbu5GegbSgdSqVgE6eOjQkPU7M0UQvR7wCEPN7XBdni7CFSL4br1k5OujCPnXyX2zBcwWHlJ/TyXsBw==","signature_status":"signed_v1","signed_at":"2026-07-04T23:56:50.827951Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.05357","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e38c3c91daf9b07d34532d3007d905d7696817f834a2f800e8e03fff8bc3370","sha256:050ca1a064f44bc5ffb262fb5379fbd385f5004b81d61360f986e9e124ba7331"],"state_sha256":"7de8ec2f8f63b745e9eec9b7f62338e985d7f1ad55f774f94ff480bf7756bbc2"}