{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:LOPAUYUEAWPTMJ37MM2FGA2A7C","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":"fe90dc706d758a999f048ee8c44b8f215d6bda185ae612baa99a8a0c1615cc17","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2015-10-21T18:21:39Z","title_canon_sha256":"98221a8342e85503d951094d324eae027fc73faeb35a075b466320b89df6eabf"},"schema_version":"1.0","source":{"id":"1510.06356","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1510.06356","created_at":"2026-05-18T01:29:37Z"},{"alias_kind":"arxiv_version","alias_value":"1510.06356v1","created_at":"2026-05-18T01:29:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.06356","created_at":"2026-05-18T01:29:37Z"},{"alias_kind":"pith_short_12","alias_value":"LOPAUYUEAWPT","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_16","alias_value":"LOPAUYUEAWPTMJ37","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_8","alias_value":"LOPAUYUE","created_at":"2026-05-18T12:29:29Z"}],"graph_snapshots":[{"event_id":"sha256:b85acd225680967c92d4d86a8716b4d4f02fed931e89085c457e52ad3b070b9e","target":"graph","created_at":"2026-05-18T01:29:37Z","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":"In Deep Learning, a well-known approach for training a Deep Neural Network starts by training a generative Deep Belief Network model, typically using Contrastive Divergence (CD), then fine-tuning the weights using backpropagation or other discriminative techniques. However, the generative training can be time-consuming due to the slow mixing of Gibbs sampling. We investigated an alternative approach that estimates model expectations of Restricted Boltzmann Machines using samples from a D-Wave quantum annealing machine. We tested this method on a coarse-grained version of the MNIST data set. In","authors_text":"Maxwell P. Henderson, Steven H. Adachi","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2015-10-21T18:21:39Z","title":"Application of Quantum Annealing to Training of Deep Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.06356","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:c71cd35fbe3e63bcb5f8e81e5abc1c25267559ebbbcef0ba818ec9846d93ce4a","target":"record","created_at":"2026-05-18T01:29:37Z","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":"fe90dc706d758a999f048ee8c44b8f215d6bda185ae612baa99a8a0c1615cc17","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2015-10-21T18:21:39Z","title_canon_sha256":"98221a8342e85503d951094d324eae027fc73faeb35a075b466320b89df6eabf"},"schema_version":"1.0","source":{"id":"1510.06356","kind":"arxiv","version":1}},"canonical_sha256":"5b9e0a6284059f36277f6334530340f8a0b1d7b37769914375ebd02011c54808","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5b9e0a6284059f36277f6334530340f8a0b1d7b37769914375ebd02011c54808","first_computed_at":"2026-05-18T01:29:37.148896Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:29:37.148896Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jSqZnBrffNlxlislTeyepdMXyvhx7w2D8mRmJLOLQro2kzhBYyNlsJpyDr6Bp9DNNQKnlxIJiKpiyG7RZB6QCA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:29:37.149485Z","signed_message":"canonical_sha256_bytes"},"source_id":"1510.06356","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c71cd35fbe3e63bcb5f8e81e5abc1c25267559ebbbcef0ba818ec9846d93ce4a","sha256:b85acd225680967c92d4d86a8716b4d4f02fed931e89085c457e52ad3b070b9e"],"state_sha256":"e7371ac172fe7a7c5cc2e6dda126551b44333c31df385096970f600aee0d3302"}