{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:Z6GRZY2R26DV35J5ALHBBHS54Q","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":"5c49591e0fbbd260527d7cd09d25cc3ecd0ff1c7aecd1a7112cc95a162974847","cross_cats_sorted":["cs.AI","cs.LG","stat.CO","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-01-16T16:33:23Z","title_canon_sha256":"09173ac70b6dc9cc3aa914d02fd1604754ab90532416983cae5ffd956c87ed65"},"schema_version":"1.0","source":{"id":"1401.4082","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1401.4082","created_at":"2026-05-18T02:50:50Z"},{"alias_kind":"arxiv_version","alias_value":"1401.4082v3","created_at":"2026-05-18T02:50:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1401.4082","created_at":"2026-05-18T02:50:50Z"},{"alias_kind":"pith_short_12","alias_value":"Z6GRZY2R26DV","created_at":"2026-05-18T12:28:59Z"},{"alias_kind":"pith_short_16","alias_value":"Z6GRZY2R26DV35J5","created_at":"2026-05-18T12:28:59Z"},{"alias_kind":"pith_short_8","alias_value":"Z6GRZY2R","created_at":"2026-05-18T12:28:59Z"}],"graph_snapshots":[{"event_id":"sha256:d94ffd49ff657ff9adcef349f9cbfdf0473aff339b33dac156e541573e0edd5e","target":"graph","created_at":"2026-05-18T02:50:50Z","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 marry ideas from deep neural networks and approximate Bayesian inference to derive a generalised class of deep, directed generative models, endowed with a new algorithm for scalable inference and learning. Our algorithm introduces a recognition model to represent approximate posterior distributions, and that acts as a stochastic encoder of the data. We develop stochastic back-propagation -- rules for back-propagation through stochastic variables -- and use this to develop an algorithm that allows for joint optimisation of the parameters of both the generative and recognition model. We demon","authors_text":"Daan Wierstra, Danilo Jimenez Rezende, Shakir Mohamed","cross_cats":["cs.AI","cs.LG","stat.CO","stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-01-16T16:33:23Z","title":"Stochastic Backpropagation and Approximate Inference in Deep Generative Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1401.4082","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":"sha256:4fb64a3dd63005a4465af92e15bde4b1555bded63cbed50187c87b3c1aac31b5","target":"record","created_at":"2026-05-18T02:50:50Z","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":"5c49591e0fbbd260527d7cd09d25cc3ecd0ff1c7aecd1a7112cc95a162974847","cross_cats_sorted":["cs.AI","cs.LG","stat.CO","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-01-16T16:33:23Z","title_canon_sha256":"09173ac70b6dc9cc3aa914d02fd1604754ab90532416983cae5ffd956c87ed65"},"schema_version":"1.0","source":{"id":"1401.4082","kind":"arxiv","version":3}},"canonical_sha256":"cf8d1ce351d7875df53d02ce109e5de428ad7bbcde3c47a12f497683574c14b5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cf8d1ce351d7875df53d02ce109e5de428ad7bbcde3c47a12f497683574c14b5","first_computed_at":"2026-05-18T02:50:50.296105Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:50:50.296105Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PsRLLHVTpiAPS9pg9DT0+hyapZunF7YUtBVgFrK9QamrD8PHM0zhqUMvftqjnSXVxcune6ZEJBEzFhFkIgzrAw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:50:50.296722Z","signed_message":"canonical_sha256_bytes"},"source_id":"1401.4082","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4fb64a3dd63005a4465af92e15bde4b1555bded63cbed50187c87b3c1aac31b5","sha256:d94ffd49ff657ff9adcef349f9cbfdf0473aff339b33dac156e541573e0edd5e"],"state_sha256":"2a77d609b07eb5c961f2cd3c44983ec69c24725f61b2ccf82be10143a99bd438"}