{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:JZTKL4BLFRP5SICFHOZ6LVTCSX","short_pith_number":"pith:JZTKL4BL","canonical_record":{"source":{"id":"1904.04917","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"stat.ML","submitted_at":"2019-04-09T21:31:08Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b403f3bafa8847c22b1832e0a46506ac75a3116f81a821d2bc4528a48f17dcd9","abstract_canon_sha256":"f97a94adfd2e4c79102765e884a347d85bd4c1d0e967ef7476af242a92c51d93"},"schema_version":"1.0"},"canonical_sha256":"4e66a5f02b2c5fd920453bb3e5d66295c46b5c7e7ac1f12df2b675058800e404","source":{"kind":"arxiv","id":"1904.04917","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.04917","created_at":"2026-05-17T23:48:57Z"},{"alias_kind":"arxiv_version","alias_value":"1904.04917v1","created_at":"2026-05-17T23:48:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.04917","created_at":"2026-05-17T23:48:57Z"},{"alias_kind":"pith_short_12","alias_value":"JZTKL4BLFRP5","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"JZTKL4BLFRP5SICF","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"JZTKL4BL","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:JZTKL4BLFRP5SICFHOZ6LVTCSX","target":"record","payload":{"canonical_record":{"source":{"id":"1904.04917","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"stat.ML","submitted_at":"2019-04-09T21:31:08Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b403f3bafa8847c22b1832e0a46506ac75a3116f81a821d2bc4528a48f17dcd9","abstract_canon_sha256":"f97a94adfd2e4c79102765e884a347d85bd4c1d0e967ef7476af242a92c51d93"},"schema_version":"1.0"},"canonical_sha256":"4e66a5f02b2c5fd920453bb3e5d66295c46b5c7e7ac1f12df2b675058800e404","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:57.691973Z","signature_b64":"eokps3YwVm62vKzPMNJK5ijuvj/7lj7xDbURyCkSzSdJ7/pp+bdSgzSDQHPMNKPaAHN241jZaAQO/iymu61iDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4e66a5f02b2c5fd920453bb3e5d66295c46b5c7e7ac1f12df2b675058800e404","last_reissued_at":"2026-05-17T23:48:57.691405Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:57.691405Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.04917","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":"2026-05-17T23:48:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A/5xPMnF/S12tr3MiDvJiuw9BMwFILTR/F2/GyueoC5U4qUb8hooDhAalvOvUAerHua+X1OutI9zVLQrHNyDBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T15:00:51.844746Z"},"content_sha256":"ce1028c0fae2e52bca36498037425cd9256f2dee01cf8eb86a09873c896b03b9","schema_version":"1.0","event_id":"sha256:ce1028c0fae2e52bca36498037425cd9256f2dee01cf8eb86a09873c896b03b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:JZTKL4BLFRP5SICFHOZ6LVTCSX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Novel Uncertainty Framework for Deep Learning Ensembles","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Michal Moshkovitz, Michal Rosen-Zvi, Tal Kachman","submitted_at":"2019-04-09T21:31:08Z","abstract_excerpt":"Deep neural networks have become the default choice for many of the machine learning tasks such as classification and regression. Dropout, a method commonly used to improve the convergence of deep neural networks, generates an ensemble of thinned networks with extensive weight sharing. Recent studies that dropout can be viewed as an approximate variational inference in Gaussian processes, and used as a practical tool to obtain uncertainty estimates of the network. We propose a novel statistical mechanics based framework to dropout and use this framework to propose a new generic algorithm that "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.04917","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":""},"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":"2026-05-17T23:48:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v/qkRMn/77vRMG2JDBVHpt4AmA7o1ZQ6nupGXeDBQ9xXoJjXiAlrqdl0E8Ve/1M9zIAVts6dm8B3hcPn5J2xAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T15:00:51.845092Z"},"content_sha256":"c84efc77f719f9a11b87523d99dcabe3fa52eff262c6fec872ea160e8ccb86b5","schema_version":"1.0","event_id":"sha256:c84efc77f719f9a11b87523d99dcabe3fa52eff262c6fec872ea160e8ccb86b5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JZTKL4BLFRP5SICFHOZ6LVTCSX/bundle.json","state_url":"https://pith.science/pith/JZTKL4BLFRP5SICFHOZ6LVTCSX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JZTKL4BLFRP5SICFHOZ6LVTCSX/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":"2026-05-28T15:00:51Z","links":{"resolver":"https://pith.science/pith/JZTKL4BLFRP5SICFHOZ6LVTCSX","bundle":"https://pith.science/pith/JZTKL4BLFRP5SICFHOZ6LVTCSX/bundle.json","state":"https://pith.science/pith/JZTKL4BLFRP5SICFHOZ6LVTCSX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JZTKL4BLFRP5SICFHOZ6LVTCSX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:JZTKL4BLFRP5SICFHOZ6LVTCSX","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":"f97a94adfd2e4c79102765e884a347d85bd4c1d0e967ef7476af242a92c51d93","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"stat.ML","submitted_at":"2019-04-09T21:31:08Z","title_canon_sha256":"b403f3bafa8847c22b1832e0a46506ac75a3116f81a821d2bc4528a48f17dcd9"},"schema_version":"1.0","source":{"id":"1904.04917","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.04917","created_at":"2026-05-17T23:48:57Z"},{"alias_kind":"arxiv_version","alias_value":"1904.04917v1","created_at":"2026-05-17T23:48:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.04917","created_at":"2026-05-17T23:48:57Z"},{"alias_kind":"pith_short_12","alias_value":"JZTKL4BLFRP5","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"JZTKL4BLFRP5SICF","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"JZTKL4BL","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:c84efc77f719f9a11b87523d99dcabe3fa52eff262c6fec872ea160e8ccb86b5","target":"graph","created_at":"2026-05-17T23:48:57Z","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":"Deep neural networks have become the default choice for many of the machine learning tasks such as classification and regression. Dropout, a method commonly used to improve the convergence of deep neural networks, generates an ensemble of thinned networks with extensive weight sharing. Recent studies that dropout can be viewed as an approximate variational inference in Gaussian processes, and used as a practical tool to obtain uncertainty estimates of the network. We propose a novel statistical mechanics based framework to dropout and use this framework to propose a new generic algorithm that ","authors_text":"Michal Moshkovitz, Michal Rosen-Zvi, Tal Kachman","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"stat.ML","submitted_at":"2019-04-09T21:31:08Z","title":"Novel Uncertainty Framework for Deep Learning Ensembles"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.04917","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:ce1028c0fae2e52bca36498037425cd9256f2dee01cf8eb86a09873c896b03b9","target":"record","created_at":"2026-05-17T23:48:57Z","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":"f97a94adfd2e4c79102765e884a347d85bd4c1d0e967ef7476af242a92c51d93","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"stat.ML","submitted_at":"2019-04-09T21:31:08Z","title_canon_sha256":"b403f3bafa8847c22b1832e0a46506ac75a3116f81a821d2bc4528a48f17dcd9"},"schema_version":"1.0","source":{"id":"1904.04917","kind":"arxiv","version":1}},"canonical_sha256":"4e66a5f02b2c5fd920453bb3e5d66295c46b5c7e7ac1f12df2b675058800e404","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4e66a5f02b2c5fd920453bb3e5d66295c46b5c7e7ac1f12df2b675058800e404","first_computed_at":"2026-05-17T23:48:57.691405Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:57.691405Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eokps3YwVm62vKzPMNJK5ijuvj/7lj7xDbURyCkSzSdJ7/pp+bdSgzSDQHPMNKPaAHN241jZaAQO/iymu61iDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:57.691973Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.04917","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ce1028c0fae2e52bca36498037425cd9256f2dee01cf8eb86a09873c896b03b9","sha256:c84efc77f719f9a11b87523d99dcabe3fa52eff262c6fec872ea160e8ccb86b5"],"state_sha256":"3c7780419177b9d73747fca70bf1409d71a2f2d53d91b0d320d094ec6e97329b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6vtOkH2tksBt01v7MoCX+PvLghrOOlSVq+4F3174v34tF0rNfL+jOEoKNzkODyR34GkAbEHSEYZ8CTtu0pr2Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T15:00:51.847984Z","bundle_sha256":"d90413dc27d3f2b4b3418ab7a18c6a2c50d96b0ef6257ec740e3a0aa815f7153"}}