{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:V46RXMTOBIWLFQ6BP3VYUPTGV4","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":"1aa250ea2e450a6172dd5d04ad8cc7877b5a55d4f627a199124887f79d350217","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-07-23T12:07:58Z","title_canon_sha256":"29fd5c1b3346d431b9b0fc60d3200c1011c44b3189b609a94073ab257c0f59bb"},"schema_version":"1.0","source":{"id":"1707.07287","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.07287","created_at":"2026-05-18T00:06:41Z"},{"alias_kind":"arxiv_version","alias_value":"1707.07287v3","created_at":"2026-05-18T00:06:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.07287","created_at":"2026-05-18T00:06:41Z"},{"alias_kind":"pith_short_12","alias_value":"V46RXMTOBIWL","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"V46RXMTOBIWLFQ6B","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"V46RXMTO","created_at":"2026-05-18T12:31:49Z"}],"graph_snapshots":[{"event_id":"sha256:7fcd20440b8331e1081f4ee737fc35d630edc41d7b88f7e3baadbe1887a60b77","target":"graph","created_at":"2026-05-18T00:06:41Z","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"},"paper":{"abstract_excerpt":"We suggest a general approach to quantification of different forms of aleatoric uncertainty in regression tasks performed by artificial neural networks. It is based on the simultaneous training of two neural networks with a joint loss function and a specific hyperparameter $\\lambda>0$ that allows for automatically detecting noisy and clean regions in the input space and controlling their {\\em relative contribution} to the loss and its gradients. After the model has been trained, one of the networks performs predictions and the other quantifies the uncertainty of these predictions by estimating","authors_text":"Hannes Stuke, Pavel Gurevich","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-07-23T12:07:58Z","title":"Pairing an arbitrary regressor with an artificial neural network estimating aleatoric uncertainty"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.07287","kind":"arxiv","version":3},"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:ec2638d831453fa75bbb02b5f11692f24a612b51c60b82a749e3d0c66f4ee57d","target":"record","created_at":"2026-05-18T00:06:41Z","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":"1aa250ea2e450a6172dd5d04ad8cc7877b5a55d4f627a199124887f79d350217","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-07-23T12:07:58Z","title_canon_sha256":"29fd5c1b3346d431b9b0fc60d3200c1011c44b3189b609a94073ab257c0f59bb"},"schema_version":"1.0","source":{"id":"1707.07287","kind":"arxiv","version":3}},"canonical_sha256":"af3d1bb26e0a2cb2c3c17eeb8a3e66af1b58de84d50f280f993c57dad7a31327","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af3d1bb26e0a2cb2c3c17eeb8a3e66af1b58de84d50f280f993c57dad7a31327","first_computed_at":"2026-05-18T00:06:41.663952Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:06:41.663952Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XJ6ynQuNlxQZTI8QrYj/z8ka1Zrtr4W9k7MGp5R51yAX+EGDwu2q2V8UOJgbMHNiqcU8lCUL6IpqYSwnLlf0DA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:06:41.664586Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.07287","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ec2638d831453fa75bbb02b5f11692f24a612b51c60b82a749e3d0c66f4ee57d","sha256:7fcd20440b8331e1081f4ee737fc35d630edc41d7b88f7e3baadbe1887a60b77"],"state_sha256":"8e016a28a41fe5290a8c10f2299ee0c853f7e62f8b425fe1cf5fc4b13f3cd85a"}