{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:T4JL5H73DI7KAMICOLFXUAB4BH","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":"48a19aa34cf3eb746448e1eb350db7c455a645c63e4521fc357ff2df1a462805","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-10-12T15:23:13Z","title_canon_sha256":"a29ef3c8015f811c9a7864d23329c5614c5c5a3e0b9c7c31b81dae54251363bf"},"schema_version":"1.0","source":{"id":"1910.05575","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.05575","created_at":"2026-07-05T00:24:41Z"},{"alias_kind":"arxiv_version","alias_value":"1910.05575v2","created_at":"2026-07-05T00:24:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.05575","created_at":"2026-07-05T00:24:41Z"},{"alias_kind":"pith_short_12","alias_value":"T4JL5H73DI7K","created_at":"2026-07-05T00:24:41Z"},{"alias_kind":"pith_short_16","alias_value":"T4JL5H73DI7KAMIC","created_at":"2026-07-05T00:24:41Z"},{"alias_kind":"pith_short_8","alias_value":"T4JL5H73","created_at":"2026-07-05T00:24:41Z"}],"graph_snapshots":[{"event_id":"sha256:ee6a4f2956e61934856857e589793ca91800c14f43dbc934ff153ab29aae873f","target":"graph","created_at":"2026-07-05T00:24:41Z","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/1910.05575/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conformal methods create prediction bands that control average coverage under no assumptions besides i.i.d. data. Besides average coverage, one might also desire to control conditional coverage, that is, coverage for every new testing point. However, without strong assumptions, conditional coverage is unachievable. Given this limitation, the literature has focused on methods with asymptotical conditional coverage. In order to obtain this property, these methods require strong conditions on the dependence between the target variable and the features. We introduce two conformal methods based on ","authors_text":"Gilson T. Shimizu, Rafael B. Stern, Rafael Izbicki","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-10-12T15:23:13Z","title":"Flexible distribution-free conditional predictive bands using density estimators"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.05575","kind":"arxiv","version":2},"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:e79d2dca8e220562526174a7d97d3527022ea2a1954bc4fd31f017d8c34f496a","target":"record","created_at":"2026-07-05T00:24:41Z","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":"48a19aa34cf3eb746448e1eb350db7c455a645c63e4521fc357ff2df1a462805","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-10-12T15:23:13Z","title_canon_sha256":"a29ef3c8015f811c9a7864d23329c5614c5c5a3e0b9c7c31b81dae54251363bf"},"schema_version":"1.0","source":{"id":"1910.05575","kind":"arxiv","version":2}},"canonical_sha256":"9f12be9ffb1a3ea0310272cb7a003c09fd86b5d4768de94c4ce4e8c792dfc0a4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9f12be9ffb1a3ea0310272cb7a003c09fd86b5d4768de94c4ce4e8c792dfc0a4","first_computed_at":"2026-07-05T00:24:41.795565Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:24:41.795565Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vmq+0KR6xAb689U3s5KGI44KZDHWpCUgP6MS0jiyPVMk0/WiVe+YMbQDcyABlW5bwWS3zXz01BUsEPoOAmyGAw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:24:41.796096Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.05575","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e79d2dca8e220562526174a7d97d3527022ea2a1954bc4fd31f017d8c34f496a","sha256:ee6a4f2956e61934856857e589793ca91800c14f43dbc934ff153ab29aae873f"],"state_sha256":"6ad58879d2c5307caf527a418659db2c30505649084dfc6227b257f6dd8007e5"}