{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:KD54D2V3U6SMI6MBL6FJUXAMGH","short_pith_number":"pith:KD54D2V3","canonical_record":{"source":{"id":"2201.13279","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-31T14:42:35Z","cross_cats_sorted":[],"title_canon_sha256":"6263e695456946923650cb7b7dcd5cb4599af99a5013639eb6b5d48b8d53e305","abstract_canon_sha256":"e29f4f8c197bb91c0218ae711746f3b4228ce90781b4f979e06df47aab1b5f07"},"schema_version":"1.0"},"canonical_sha256":"50fbc1eabba7a4c479815f8a9a5c0c31ebdd12edccf89e49b1137d53175de818","source":{"kind":"arxiv","id":"2201.13279","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.13279","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"arxiv_version","alias_value":"2201.13279v5","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.13279","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"pith_short_12","alias_value":"KD54D2V3U6SM","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"pith_short_16","alias_value":"KD54D2V3U6SMI6MB","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"pith_short_8","alias_value":"KD54D2V3","created_at":"2026-07-05T05:31:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:KD54D2V3U6SMI6MBL6FJUXAMGH","target":"record","payload":{"canonical_record":{"source":{"id":"2201.13279","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-31T14:42:35Z","cross_cats_sorted":[],"title_canon_sha256":"6263e695456946923650cb7b7dcd5cb4599af99a5013639eb6b5d48b8d53e305","abstract_canon_sha256":"e29f4f8c197bb91c0218ae711746f3b4228ce90781b4f979e06df47aab1b5f07"},"schema_version":"1.0"},"canonical_sha256":"50fbc1eabba7a4c479815f8a9a5c0c31ebdd12edccf89e49b1137d53175de818","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:31:12.621136Z","signature_b64":"ml4D/FdBOhqWatk0FiERZy80J5W23GQwifeCz03Ap0kDZdSR27r5RkVcovLZV5eNk8TXfeVdRBf6EiRRq/F6DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"50fbc1eabba7a4c479815f8a9a5c0c31ebdd12edccf89e49b1137d53175de818","last_reissued_at":"2026-07-05T05:31:12.620600Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:31:12.620600Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2201.13279","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:31:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"twpnrdL7QRiRmscVvOfhrx9lgHotD38WYrw4zZQh3BI5QKSv+RKQ+Oie+kofgyY+c5wnLam/zvIz+T/bv6fFCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T02:10:49.915910Z"},"content_sha256":"89821c9c5f30fd0e4d4a5d599b26273f66cc8e3c174da39d9e1cf0d40883981b","schema_version":"1.0","event_id":"sha256:89821c9c5f30fd0e4d4a5d599b26273f66cc8e3c174da39d9e1cf0d40883981b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:KD54D2V3U6SMI6MBL6FJUXAMGH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Gernot A. Fink, Matthias Rottmann, Philipp Oberdiek","submitted_at":"2022-01-31T14:42:35Z","abstract_excerpt":"We present an approach to quantifying both aleatoric and epistemic uncertainty for deep neural networks in image classification, based on generative adversarial networks (GANs). While most works in the literature that use GANs to generate out-of-distribution (OoD) examples only focus on the evaluation of OoD detection, we present a GAN based approach to learn a classifier that produces proper uncertainties for OoD examples as well as for false positives (FPs). Instead of shielding the entire in-distribution data with GAN generated OoD examples which is state-of-the-art, we shield each class se"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.13279","kind":"arxiv","version":5},"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/2201.13279/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:31:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qSCaLho+Cbna9hlO4iFugoYEtOIRUHRmGL5pwS/6sDJRbNj3KHZZFgN5abdvdnsKoseArHC46emitzIXkqOfAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T02:10:49.916779Z"},"content_sha256":"45598468b866f94d11d2e29a186e9dbcee43dd23ad8b1a1b3082c606e7a0bf13","schema_version":"1.0","event_id":"sha256:45598468b866f94d11d2e29a186e9dbcee43dd23ad8b1a1b3082c606e7a0bf13"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KD54D2V3U6SMI6MBL6FJUXAMGH/bundle.json","state_url":"https://pith.science/pith/KD54D2V3U6SMI6MBL6FJUXAMGH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KD54D2V3U6SMI6MBL6FJUXAMGH/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-11T02:10:49Z","links":{"resolver":"https://pith.science/pith/KD54D2V3U6SMI6MBL6FJUXAMGH","bundle":"https://pith.science/pith/KD54D2V3U6SMI6MBL6FJUXAMGH/bundle.json","state":"https://pith.science/pith/KD54D2V3U6SMI6MBL6FJUXAMGH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KD54D2V3U6SMI6MBL6FJUXAMGH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:KD54D2V3U6SMI6MBL6FJUXAMGH","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":"e29f4f8c197bb91c0218ae711746f3b4228ce90781b4f979e06df47aab1b5f07","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-31T14:42:35Z","title_canon_sha256":"6263e695456946923650cb7b7dcd5cb4599af99a5013639eb6b5d48b8d53e305"},"schema_version":"1.0","source":{"id":"2201.13279","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.13279","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"arxiv_version","alias_value":"2201.13279v5","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.13279","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"pith_short_12","alias_value":"KD54D2V3U6SM","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"pith_short_16","alias_value":"KD54D2V3U6SMI6MB","created_at":"2026-07-05T05:31:12Z"},{"alias_kind":"pith_short_8","alias_value":"KD54D2V3","created_at":"2026-07-05T05:31:12Z"}],"graph_snapshots":[{"event_id":"sha256:45598468b866f94d11d2e29a186e9dbcee43dd23ad8b1a1b3082c606e7a0bf13","target":"graph","created_at":"2026-07-05T05:31:12Z","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/2201.13279/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present an approach to quantifying both aleatoric and epistemic uncertainty for deep neural networks in image classification, based on generative adversarial networks (GANs). While most works in the literature that use GANs to generate out-of-distribution (OoD) examples only focus on the evaluation of OoD detection, we present a GAN based approach to learn a classifier that produces proper uncertainties for OoD examples as well as for false positives (FPs). Instead of shielding the entire in-distribution data with GAN generated OoD examples which is state-of-the-art, we shield each class se","authors_text":"Gernot A. Fink, Matthias Rottmann, Philipp Oberdiek","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-31T14:42:35Z","title":"UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.13279","kind":"arxiv","version":5},"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":"sha256:89821c9c5f30fd0e4d4a5d599b26273f66cc8e3c174da39d9e1cf0d40883981b","target":"record","created_at":"2026-07-05T05:31:12Z","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":"e29f4f8c197bb91c0218ae711746f3b4228ce90781b4f979e06df47aab1b5f07","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-31T14:42:35Z","title_canon_sha256":"6263e695456946923650cb7b7dcd5cb4599af99a5013639eb6b5d48b8d53e305"},"schema_version":"1.0","source":{"id":"2201.13279","kind":"arxiv","version":5}},"canonical_sha256":"50fbc1eabba7a4c479815f8a9a5c0c31ebdd12edccf89e49b1137d53175de818","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"50fbc1eabba7a4c479815f8a9a5c0c31ebdd12edccf89e49b1137d53175de818","first_computed_at":"2026-07-05T05:31:12.620600Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:31:12.620600Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ml4D/FdBOhqWatk0FiERZy80J5W23GQwifeCz03Ap0kDZdSR27r5RkVcovLZV5eNk8TXfeVdRBf6EiRRq/F6DA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:31:12.621136Z","signed_message":"canonical_sha256_bytes"},"source_id":"2201.13279","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:89821c9c5f30fd0e4d4a5d599b26273f66cc8e3c174da39d9e1cf0d40883981b","sha256:45598468b866f94d11d2e29a186e9dbcee43dd23ad8b1a1b3082c606e7a0bf13"],"state_sha256":"6f8b6bc97cc17541c0985450c4c9c7afff9cd9903616b56312cb3ad76f928805"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yJsMlGhZG7u1g9KuYo5kXvK7urmYVdlNGaTBqU1T8pIznvpwZ+/jAWmCOTJw8bKqRnX9UjE1/4xHsX2yqaHHBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T02:10:49.925572Z","bundle_sha256":"becd725d844cc88117edad0d2f24f0667fa9e785b996f0e5a95a56c0d6545815"}}