{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:F7BAUWTKJBCTXKGDM35ZQMROLE","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":"42c7b4e71049f45a7a1b40d9a3eb037d159cf05455e17a1b8d68edae08dcd32f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-30T19:53:11Z","title_canon_sha256":"5bcd2febd2b4e0d692b9df002d77e7325ba85a1a835f77c77415b0b3a04cfefb"},"schema_version":"1.0","source":{"id":"1609.09869","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.09869","created_at":"2026-05-18T00:55:57Z"},{"alias_kind":"arxiv_version","alias_value":"1609.09869v2","created_at":"2026-05-18T00:55:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.09869","created_at":"2026-05-18T00:55:57Z"},{"alias_kind":"pith_short_12","alias_value":"F7BAUWTKJBCT","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"F7BAUWTKJBCTXKGD","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"F7BAUWTK","created_at":"2026-05-18T12:30:15Z"}],"graph_snapshots":[{"event_id":"sha256:24de558cd68caeb78d4ac76fc2cbbe1d79bd0f1360600cf051ba4fbf11708eaf","target":"graph","created_at":"2026-05-18T00:55:57Z","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":"Gaussian state space models have been used for decades as generative models of sequential data. They admit an intuitive probabilistic interpretation, have a simple functional form, and enjoy widespread adoption. We introduce a unified algorithm to efficiently learn a broad class of linear and non-linear state space models, including variants where the emission and transition distributions are modeled by deep neural networks. Our learning algorithm simultaneously learns a compiled inference network and the generative model, leveraging a structured variational approximation parameterized by recu","authors_text":"David Sontag, Rahul G. Krishnan, Uri Shalit","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-30T19:53:11Z","title":"Structured Inference Networks for Nonlinear State Space Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.09869","kind":"arxiv","version":2},"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":"sha256:76422078f34d8e012ca306f22658cabd0ca63f8eb2a32d9b1a9edfe2b4babb2f","target":"record","created_at":"2026-05-18T00:55:57Z","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":"42c7b4e71049f45a7a1b40d9a3eb037d159cf05455e17a1b8d68edae08dcd32f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-30T19:53:11Z","title_canon_sha256":"5bcd2febd2b4e0d692b9df002d77e7325ba85a1a835f77c77415b0b3a04cfefb"},"schema_version":"1.0","source":{"id":"1609.09869","kind":"arxiv","version":2}},"canonical_sha256":"2fc20a5a6a48453ba8c366fb98322e5909584f10dc3da6162bca8f85d7dc451c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2fc20a5a6a48453ba8c366fb98322e5909584f10dc3da6162bca8f85d7dc451c","first_computed_at":"2026-05-18T00:55:57.571035Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:55:57.571035Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ub/StbzKNbD2mKkYx/4Qqe8MmKo/1WcW9RVkrHO/QYfu8+bFKKKHM0lLCVa4tWwMxQdwCJrRwd2OW8CSyCw+Bg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:55:57.571525Z","signed_message":"canonical_sha256_bytes"},"source_id":"1609.09869","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:76422078f34d8e012ca306f22658cabd0ca63f8eb2a32d9b1a9edfe2b4babb2f","sha256:24de558cd68caeb78d4ac76fc2cbbe1d79bd0f1360600cf051ba4fbf11708eaf"],"state_sha256":"ee1b860ed777ef992a59984a6f8f778c71efba5199b726f1c0d26ee1fba0247d"}