{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:HDR244KO2QMAZ6MBZWFWEOIBDP","short_pith_number":"pith:HDR244KO","canonical_record":{"source":{"id":"2103.00668","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-03-01T00:17:53Z","cross_cats_sorted":["cs.LG","cs.PL"],"title_canon_sha256":"a6b8966a081bfd58dbd8a387322b72b1babda004c0f07abd8abb95c76ee6e1ae","abstract_canon_sha256":"7f1c4f57eeca40dcb6b6401f7bfc3dd892a376babd240c29d31fa4a76209ebfc"},"schema_version":"1.0"},"canonical_sha256":"38e3ae714ed4180cf981cd8b6239011bce5287aef1d1122707f4807b7bf95484","source":{"kind":"arxiv","id":"2103.00668","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.00668","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"arxiv_version","alias_value":"2103.00668v3","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.00668","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"pith_short_12","alias_value":"HDR244KO2QMA","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"pith_short_16","alias_value":"HDR244KO2QMAZ6MB","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"pith_short_8","alias_value":"HDR244KO","created_at":"2026-07-05T02:50:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:HDR244KO2QMAZ6MBZWFWEOIBDP","target":"record","payload":{"canonical_record":{"source":{"id":"2103.00668","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-03-01T00:17:53Z","cross_cats_sorted":["cs.LG","cs.PL"],"title_canon_sha256":"a6b8966a081bfd58dbd8a387322b72b1babda004c0f07abd8abb95c76ee6e1ae","abstract_canon_sha256":"7f1c4f57eeca40dcb6b6401f7bfc3dd892a376babd240c29d31fa4a76209ebfc"},"schema_version":"1.0"},"canonical_sha256":"38e3ae714ed4180cf981cd8b6239011bce5287aef1d1122707f4807b7bf95484","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:50:09.626179Z","signature_b64":"o5CqArTC/yqaPfJgJ77Mc4SY5jCyM/Ph0iaixGhRBEeCY2S6U9WoQsLuPqFmdvnpdb8sEWIahWiu9l5YfJBTBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"38e3ae714ed4180cf981cd8b6239011bce5287aef1d1122707f4807b7bf95484","last_reissued_at":"2026-07-05T02:50:09.625555Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:50:09.625555Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2103.00668","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:50:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i3EQO3w4QPwo93QFWAXK2oRqOe58LeeghRdvjG8TGqb/oGhHEdXalpOuEAaB9gMs5Lh8iGZH+oR+ZaSo6qFnAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:37:31.931207Z"},"content_sha256":"3572047dda524afd6044f90bb9485743ca7778a1bb8378840fb76eeacf5c6dc6","schema_version":"1.0","event_id":"sha256:3572047dda524afd6044f90bb9485743ca7778a1bb8378840fb76eeacf5c6dc6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:HDR244KO2QMAZ6MBZWFWEOIBDP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Proposals for Probabilistic Programs with Inference Combinators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.PL"],"primary_cat":"stat.ML","authors_text":"Eli Sennesh, Hao Wu, Heiko Zimmermann, Jan-Willem van de Meent, Sam Stites","submitted_at":"2021-03-01T00:17:53Z","abstract_excerpt":"We develop operators for construction of proposals in probabilistic programs, which we refer to as inference combinators. Inference combinators define a grammar over importance samplers that compose primitive operations such as application of a transition kernel and importance resampling. Proposals in these samplers can be parameterized using neural networks, which in turn can be trained by optimizing variational objectives. The result is a framework for user-programmable variational methods that are correct by construction and can be tailored to specific models. We demonstrate the flexibility"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.00668","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2103.00668/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T02:50:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/J9D25Hq/czgyNfCchmUBKe5euz0Bu2tQJ+c5HNsjqUNsi+wG3O3f+6wEu1BCYu7m/CG1JeJb/eKfAB59O8qDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:37:31.931603Z"},"content_sha256":"af9a1c3e3ea21f2e2b38230ee1e4c8700c7d211154ac035f1235d37233996da3","schema_version":"1.0","event_id":"sha256:af9a1c3e3ea21f2e2b38230ee1e4c8700c7d211154ac035f1235d37233996da3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HDR244KO2QMAZ6MBZWFWEOIBDP/bundle.json","state_url":"https://pith.science/pith/HDR244KO2QMAZ6MBZWFWEOIBDP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HDR244KO2QMAZ6MBZWFWEOIBDP/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":"2026-07-06T19:37:31Z","links":{"resolver":"https://pith.science/pith/HDR244KO2QMAZ6MBZWFWEOIBDP","bundle":"https://pith.science/pith/HDR244KO2QMAZ6MBZWFWEOIBDP/bundle.json","state":"https://pith.science/pith/HDR244KO2QMAZ6MBZWFWEOIBDP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HDR244KO2QMAZ6MBZWFWEOIBDP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:HDR244KO2QMAZ6MBZWFWEOIBDP","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":"7f1c4f57eeca40dcb6b6401f7bfc3dd892a376babd240c29d31fa4a76209ebfc","cross_cats_sorted":["cs.LG","cs.PL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-03-01T00:17:53Z","title_canon_sha256":"a6b8966a081bfd58dbd8a387322b72b1babda004c0f07abd8abb95c76ee6e1ae"},"schema_version":"1.0","source":{"id":"2103.00668","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.00668","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"arxiv_version","alias_value":"2103.00668v3","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.00668","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"pith_short_12","alias_value":"HDR244KO2QMA","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"pith_short_16","alias_value":"HDR244KO2QMAZ6MB","created_at":"2026-07-05T02:50:09Z"},{"alias_kind":"pith_short_8","alias_value":"HDR244KO","created_at":"2026-07-05T02:50:09Z"}],"graph_snapshots":[{"event_id":"sha256:af9a1c3e3ea21f2e2b38230ee1e4c8700c7d211154ac035f1235d37233996da3","target":"graph","created_at":"2026-07-05T02:50:09Z","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/2103.00668/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We develop operators for construction of proposals in probabilistic programs, which we refer to as inference combinators. Inference combinators define a grammar over importance samplers that compose primitive operations such as application of a transition kernel and importance resampling. Proposals in these samplers can be parameterized using neural networks, which in turn can be trained by optimizing variational objectives. The result is a framework for user-programmable variational methods that are correct by construction and can be tailored to specific models. We demonstrate the flexibility","authors_text":"Eli Sennesh, Hao Wu, Heiko Zimmermann, Jan-Willem van de Meent, Sam Stites","cross_cats":["cs.LG","cs.PL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-03-01T00:17:53Z","title":"Learning Proposals for Probabilistic Programs with Inference Combinators"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.00668","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":"sha256:3572047dda524afd6044f90bb9485743ca7778a1bb8378840fb76eeacf5c6dc6","target":"record","created_at":"2026-07-05T02:50:09Z","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":"7f1c4f57eeca40dcb6b6401f7bfc3dd892a376babd240c29d31fa4a76209ebfc","cross_cats_sorted":["cs.LG","cs.PL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2021-03-01T00:17:53Z","title_canon_sha256":"a6b8966a081bfd58dbd8a387322b72b1babda004c0f07abd8abb95c76ee6e1ae"},"schema_version":"1.0","source":{"id":"2103.00668","kind":"arxiv","version":3}},"canonical_sha256":"38e3ae714ed4180cf981cd8b6239011bce5287aef1d1122707f4807b7bf95484","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"38e3ae714ed4180cf981cd8b6239011bce5287aef1d1122707f4807b7bf95484","first_computed_at":"2026-07-05T02:50:09.625555Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:50:09.625555Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"o5CqArTC/yqaPfJgJ77Mc4SY5jCyM/Ph0iaixGhRBEeCY2S6U9WoQsLuPqFmdvnpdb8sEWIahWiu9l5YfJBTBw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:50:09.626179Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.00668","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3572047dda524afd6044f90bb9485743ca7778a1bb8378840fb76eeacf5c6dc6","sha256:af9a1c3e3ea21f2e2b38230ee1e4c8700c7d211154ac035f1235d37233996da3"],"state_sha256":"224a31755a9a780b04ae316916d9c1b12fa929010e28c21395e0871ea3cf8da4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EASkYLX55D47OcKYuAkQ1vUXpqrknOhK4maf38lA3WLxpNfLA26D84Cr5/x7OxjvQDdquTNnWo5vrcPSMieZBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T19:37:31.933531Z","bundle_sha256":"8c247a017ae47351c3392179049eda3fd8312c352c5acfb6701edda3087d974f"}}