{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:NZCFZB35QZ5CW562O6B7HWQ4GV","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":"818ed960d0ec977085c159fe13c14f8e0c32ff2daf201f60447edb711eadf018","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2020-07-20T03:46:36Z","title_canon_sha256":"a5f4e9eb0b02d9c3acadeeab0aa33738b4b8b5dc8c85e93d563274df4069057b"},"schema_version":"1.0","source":{"id":"2007.09871","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2007.09871","created_at":"2026-07-05T01:20:37Z"},{"alias_kind":"arxiv_version","alias_value":"2007.09871v2","created_at":"2026-07-05T01:20:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.09871","created_at":"2026-07-05T01:20:37Z"},{"alias_kind":"pith_short_12","alias_value":"NZCFZB35QZ5C","created_at":"2026-07-05T01:20:37Z"},{"alias_kind":"pith_short_16","alias_value":"NZCFZB35QZ5CW562","created_at":"2026-07-05T01:20:37Z"},{"alias_kind":"pith_short_8","alias_value":"NZCFZB35","created_at":"2026-07-05T01:20:37Z"}],"graph_snapshots":[{"event_id":"sha256:fed67b61f1b2e2626c24a8722a03e50059ab2f8f9c480b0611e217691d8700ea","target":"graph","created_at":"2026-07-05T01:20:37Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2007.09871/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Involutive MCMC is a unifying mathematical construction for MCMC kernels that generalizes many classic and state-of-the-art MCMC algorithms, from reversible jump MCMC to kernels based on deep neural networks. But as with MCMC samplers more generally, implementing involutive MCMC kernels is often tedious and error-prone, especially when sampling on complex state spaces. This paper describes a technique for automating the implementation of involutive MCMC kernels given (i) a pair of probabilistic programs defining the target distribution and an auxiliary distribution respectively and (ii) a diff","authors_text":"Alexander K. Lew, Marco Cusumano-Towner, Vikash K. Mansinghka","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2020-07-20T03:46:36Z","title":"Automating Involutive MCMC using Probabilistic and Differentiable Programming"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.09871","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":"sha256:16e7cbd1bbd441621e9226098f0575e53e91eb0a8b300a150b0707e7392b2c36","target":"record","created_at":"2026-07-05T01:20:37Z","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":"818ed960d0ec977085c159fe13c14f8e0c32ff2daf201f60447edb711eadf018","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2020-07-20T03:46:36Z","title_canon_sha256":"a5f4e9eb0b02d9c3acadeeab0aa33738b4b8b5dc8c85e93d563274df4069057b"},"schema_version":"1.0","source":{"id":"2007.09871","kind":"arxiv","version":2}},"canonical_sha256":"6e445c877d867a2b77da7783f3da1c356e3d4a8e9c8c0ccafa1e9a94e54aaf8b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6e445c877d867a2b77da7783f3da1c356e3d4a8e9c8c0ccafa1e9a94e54aaf8b","first_computed_at":"2026-07-05T01:20:37.604678Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:20:37.604678Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"93TnhP5dMbdDFf59wUjBJyG3YMjBwCrx+BXNZnaKk3vvW2roBxCosigyDXmL4dcv/O/9l6+ajpZolqCofeO1CA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:20:37.605250Z","signed_message":"canonical_sha256_bytes"},"source_id":"2007.09871","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:16e7cbd1bbd441621e9226098f0575e53e91eb0a8b300a150b0707e7392b2c36","sha256:fed67b61f1b2e2626c24a8722a03e50059ab2f8f9c480b0611e217691d8700ea"],"state_sha256":"e4d5cf2801ae6292f3e9b996a8e56cde75a1b3edc21f9632a30c67cdee39750d"}