{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:G45JBWQ3JVPSGS4E2KWTUUTSZD","short_pith_number":"pith:G45JBWQ3","canonical_record":{"source":{"id":"2206.07609","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-06-15T15:39:52Z","cross_cats_sorted":["cs.NE","stat.ML"],"title_canon_sha256":"71f57db165cf38cfca0dd512883066590dec14fc6a89c929e7599e7611fe2914","abstract_canon_sha256":"0afc5a88be68edd0e91ea702407222afa5c3eb400e7e94f9b3fa55e66bf30514"},"schema_version":"1.0"},"canonical_sha256":"373a90da1b4d5f234b84d2ad3a5272c8dc130d9d95211fadee86a6a52ac113c2","source":{"kind":"arxiv","id":"2206.07609","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.07609","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"arxiv_version","alias_value":"2206.07609v1","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.07609","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"pith_short_12","alias_value":"G45JBWQ3JVPS","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"pith_short_16","alias_value":"G45JBWQ3JVPSGS4E","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"pith_short_8","alias_value":"G45JBWQ3","created_at":"2026-07-05T04:32:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:G45JBWQ3JVPSGS4E2KWTUUTSZD","target":"record","payload":{"canonical_record":{"source":{"id":"2206.07609","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-06-15T15:39:52Z","cross_cats_sorted":["cs.NE","stat.ML"],"title_canon_sha256":"71f57db165cf38cfca0dd512883066590dec14fc6a89c929e7599e7611fe2914","abstract_canon_sha256":"0afc5a88be68edd0e91ea702407222afa5c3eb400e7e94f9b3fa55e66bf30514"},"schema_version":"1.0"},"canonical_sha256":"373a90da1b4d5f234b84d2ad3a5272c8dc130d9d95211fadee86a6a52ac113c2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:32:06.882768Z","signature_b64":"Z1WbRiXnmHPUN4xlvw7notivd91hqrejnRMNN7O6WHW6PPORsmp7l6bOL1r5US0Oegi5wJEyalFZAuYRmdeYDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"373a90da1b4d5f234b84d2ad3a5272c8dc130d9d95211fadee86a6a52ac113c2","last_reissued_at":"2026-07-05T04:32:06.882297Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:32:06.882297Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2206.07609","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:32:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zq1YQgcofrHWWQlTg3cIcu5eemoJNx5jbFZ7XSGcAW5lPTgbyjCB3bduXP3Ran2Lz0aDVjesA8ZIpTP3/smADg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T06:15:05.230403Z"},"content_sha256":"fc9424ee496af665a066fad479a409247b58a6c37cb24727a96c4b5c79ea7034","schema_version":"1.0","event_id":"sha256:fc9424ee496af665a066fad479a409247b58a6c37cb24727a96c4b5c79ea7034"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:G45JBWQ3JVPSGS4E2KWTUUTSZD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Epistemic Deep Learning","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.NE","stat.ML"],"primary_cat":"cs.LG","authors_text":"Fabio Cuzzolin, Shireen Kudukkil Manchingal","submitted_at":"2022-06-15T15:39:52Z","abstract_excerpt":"The belief function approach to uncertainty quantification as proposed in the Demspter-Shafer theory of evidence is established upon the general mathematical models for set-valued observations, called random sets. Set-valued predictions are the most natural representations of uncertainty in machine learning. In this paper, we introduce a concept called epistemic deep learning based on the random-set interpretation of belief functions to model epistemic learning in deep neural networks. We propose a novel random-set convolutional neural network for classification that produces scores for sets o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.07609","kind":"arxiv","version":1},"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/2206.07609/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":"2026-07-05T04:32:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I7M3mmiZF78PAIqysbTOpA0/GPW2WP3mBQVk5w0asrr+trH15QJSly0zgWNcg7chc5NcD0weJcVoQPyXUGH8BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T06:15:05.230933Z"},"content_sha256":"a648ee512a3b164faaf4e8d6a00c16f76ede6b125561e50ddd2e8e508d3481e3","schema_version":"1.0","event_id":"sha256:a648ee512a3b164faaf4e8d6a00c16f76ede6b125561e50ddd2e8e508d3481e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G45JBWQ3JVPSGS4E2KWTUUTSZD/bundle.json","state_url":"https://pith.science/pith/G45JBWQ3JVPSGS4E2KWTUUTSZD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G45JBWQ3JVPSGS4E2KWTUUTSZD/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":"2026-08-11T06:15:05Z","links":{"resolver":"https://pith.science/pith/G45JBWQ3JVPSGS4E2KWTUUTSZD","bundle":"https://pith.science/pith/G45JBWQ3JVPSGS4E2KWTUUTSZD/bundle.json","state":"https://pith.science/pith/G45JBWQ3JVPSGS4E2KWTUUTSZD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G45JBWQ3JVPSGS4E2KWTUUTSZD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:G45JBWQ3JVPSGS4E2KWTUUTSZD","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":"0afc5a88be68edd0e91ea702407222afa5c3eb400e7e94f9b3fa55e66bf30514","cross_cats_sorted":["cs.NE","stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-06-15T15:39:52Z","title_canon_sha256":"71f57db165cf38cfca0dd512883066590dec14fc6a89c929e7599e7611fe2914"},"schema_version":"1.0","source":{"id":"2206.07609","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.07609","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"arxiv_version","alias_value":"2206.07609v1","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.07609","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"pith_short_12","alias_value":"G45JBWQ3JVPS","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"pith_short_16","alias_value":"G45JBWQ3JVPSGS4E","created_at":"2026-07-05T04:32:06Z"},{"alias_kind":"pith_short_8","alias_value":"G45JBWQ3","created_at":"2026-07-05T04:32:06Z"}],"graph_snapshots":[{"event_id":"sha256:a648ee512a3b164faaf4e8d6a00c16f76ede6b125561e50ddd2e8e508d3481e3","target":"graph","created_at":"2026-07-05T04:32:06Z","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/2206.07609/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The belief function approach to uncertainty quantification as proposed in the Demspter-Shafer theory of evidence is established upon the general mathematical models for set-valued observations, called random sets. Set-valued predictions are the most natural representations of uncertainty in machine learning. In this paper, we introduce a concept called epistemic deep learning based on the random-set interpretation of belief functions to model epistemic learning in deep neural networks. We propose a novel random-set convolutional neural network for classification that produces scores for sets o","authors_text":"Fabio Cuzzolin, Shireen Kudukkil Manchingal","cross_cats":["cs.NE","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-06-15T15:39:52Z","title":"Epistemic Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.07609","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:fc9424ee496af665a066fad479a409247b58a6c37cb24727a96c4b5c79ea7034","target":"record","created_at":"2026-07-05T04:32:06Z","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":"0afc5a88be68edd0e91ea702407222afa5c3eb400e7e94f9b3fa55e66bf30514","cross_cats_sorted":["cs.NE","stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-06-15T15:39:52Z","title_canon_sha256":"71f57db165cf38cfca0dd512883066590dec14fc6a89c929e7599e7611fe2914"},"schema_version":"1.0","source":{"id":"2206.07609","kind":"arxiv","version":1}},"canonical_sha256":"373a90da1b4d5f234b84d2ad3a5272c8dc130d9d95211fadee86a6a52ac113c2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"373a90da1b4d5f234b84d2ad3a5272c8dc130d9d95211fadee86a6a52ac113c2","first_computed_at":"2026-07-05T04:32:06.882297Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:32:06.882297Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z1WbRiXnmHPUN4xlvw7notivd91hqrejnRMNN7O6WHW6PPORsmp7l6bOL1r5US0Oegi5wJEyalFZAuYRmdeYDw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:32:06.882768Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.07609","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fc9424ee496af665a066fad479a409247b58a6c37cb24727a96c4b5c79ea7034","sha256:a648ee512a3b164faaf4e8d6a00c16f76ede6b125561e50ddd2e8e508d3481e3"],"state_sha256":"8f5cfaa6eafef7319cbde57e9fd2545e4efc454d8695d984e5973a247d556508"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CZ9Rw8EivlNB0zDuS0OtTyBQCIYPeXPkduUSMmZ0SwoFO12E+mEC4U6bKwv6D7M2cm5KMZ7IKSIRICjCBl5uBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T06:15:05.236930Z","bundle_sha256":"10e92e5756ae4f2c522d68fa6a12d2a7159b3048bf6d469b170a4f3a6e09a2be"}}