{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:H3HMGN5NL56N52W7IFOLCTGFZH","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":"fea9b8e33bf6457c7419bd49ee0ae13fd81803ea69dabe24ac6b71631f0a678f","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-01T07:17:38Z","title_canon_sha256":"dea5a87df494723c0d4463aef14b859c31e334e3e7a3190cafaaf3fa98eff614"},"schema_version":"1.0","source":{"id":"2406.00332","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.00332","created_at":"2026-07-05T08:26:00Z"},{"alias_kind":"arxiv_version","alias_value":"2406.00332v1","created_at":"2026-07-05T08:26:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.00332","created_at":"2026-07-05T08:26:00Z"},{"alias_kind":"pith_short_12","alias_value":"H3HMGN5NL56N","created_at":"2026-07-05T08:26:00Z"},{"alias_kind":"pith_short_16","alias_value":"H3HMGN5NL56N52W7","created_at":"2026-07-05T08:26:00Z"},{"alias_kind":"pith_short_8","alias_value":"H3HMGN5N","created_at":"2026-07-05T08:26:00Z"}],"graph_snapshots":[{"event_id":"sha256:55de39ae23f062341fa2bb398cfe1c3f261db1310c21cf6d559e5715f608f5bf","target":"graph","created_at":"2026-07-05T08:26:00Z","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/2406.00332/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The adaptation and use of Machine Learning (ML) in our daily lives has led to concerns in lack of transparency, privacy, reliability, among others. As a result, we are seeing research in niche areas such as interpretability, causality, bias and fairness, and reliability. In this survey paper, we focus on a critical concern for adaptation of ML in risk-sensitive applications, namely understanding and quantifying uncertainty. Our paper approaches this topic in a structured way, providing a review of the literature in the various facets that uncertainty is enveloped in the ML process. We begin by","authors_text":"Ali Mosleh, Fahimeh Fakour, Ramin Ramezani","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-01T07:17:38Z","title":"A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.00332","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:d0104d461d66d5052bb19d65f3919dcb1b9344a610f077b4fbe417431c7f0733","target":"record","created_at":"2026-07-05T08:26:00Z","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":"fea9b8e33bf6457c7419bd49ee0ae13fd81803ea69dabe24ac6b71631f0a678f","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-01T07:17:38Z","title_canon_sha256":"dea5a87df494723c0d4463aef14b859c31e334e3e7a3190cafaaf3fa98eff614"},"schema_version":"1.0","source":{"id":"2406.00332","kind":"arxiv","version":1}},"canonical_sha256":"3ecec337ad5f7cdeeadf415cb14cc5c9fb1591d670ae1f1b6ab1b3169d255ff1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3ecec337ad5f7cdeeadf415cb14cc5c9fb1591d670ae1f1b6ab1b3169d255ff1","first_computed_at":"2026-07-05T08:26:00.279397Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:26:00.279397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"crJFSYOz3IZua3Y3VV+0Mkm9ebbmLKQaS5XJj+qdMMSGER70C8/tMSF+juKVkgZt3MPjYjJJd2RVK3fUvCXmCA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:26:00.279848Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.00332","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d0104d461d66d5052bb19d65f3919dcb1b9344a610f077b4fbe417431c7f0733","sha256:55de39ae23f062341fa2bb398cfe1c3f261db1310c21cf6d559e5715f608f5bf"],"state_sha256":"13f53251598930c1eb6f9566816049940903f0fd5a0255c04384d223fb64b24b"}