{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:J3KQSGSVJ7NXT66GSP3JGQXNEL","short_pith_number":"pith:J3KQSGSV","canonical_record":{"source":{"id":"2011.05836","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-11-11T14:59:34Z","cross_cats_sorted":["cs.LG","hep-ex","hep-ph","physics.data-an"],"title_canon_sha256":"7dd6745bd9877ce5a789a5d8f64bb750e8da14ac256b913ed407eb2008759a0b","abstract_canon_sha256":"cf68ca628709ea17acb22b5304c822b3e03e138972b7834ec779a3cec8c9d4f1"},"schema_version":"1.0"},"canonical_sha256":"4ed5091a554fdb79fbc693f69342ed22e589b7ce72de2cd00c338840d73b8e53","source":{"kind":"arxiv","id":"2011.05836","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.05836","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"arxiv_version","alias_value":"2011.05836v2","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.05836","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"pith_short_12","alias_value":"J3KQSGSVJ7NX","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"pith_short_16","alias_value":"J3KQSGSVJ7NXT66G","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"pith_short_8","alias_value":"J3KQSGSV","created_at":"2026-07-05T02:18:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:J3KQSGSVJ7NXT66GSP3JGQXNEL","target":"record","payload":{"canonical_record":{"source":{"id":"2011.05836","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-11-11T14:59:34Z","cross_cats_sorted":["cs.LG","hep-ex","hep-ph","physics.data-an"],"title_canon_sha256":"7dd6745bd9877ce5a789a5d8f64bb750e8da14ac256b913ed407eb2008759a0b","abstract_canon_sha256":"cf68ca628709ea17acb22b5304c822b3e03e138972b7834ec779a3cec8c9d4f1"},"schema_version":"1.0"},"canonical_sha256":"4ed5091a554fdb79fbc693f69342ed22e589b7ce72de2cd00c338840d73b8e53","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:18:57.672152Z","signature_b64":"kvnFUA9L9ccO3J9jJDMmPknGXXdDaww/7E1pWLSI66ZExzxB/38ML3eSl11t3VQZk9yPTRmyRsFQGk5X4QcyDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4ed5091a554fdb79fbc693f69342ed22e589b7ce72de2cd00c338840d73b8e53","last_reissued_at":"2026-07-05T02:18:57.671685Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:18:57.671685Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.05836","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:18:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/IvhN3mDxHdyWvYIR/DCyY5Lj+GqAYoW95ioNVrZexS8EDHe6IMgGpzE+CLz9Ag/tTzrUA69RDmg2UQJoQ9OBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T21:41:52.739897Z"},"content_sha256":"99fc121d491f46b38c49b8309f3bda06a695a3e9feff64951fea5b6c55be9f88","schema_version":"1.0","event_id":"sha256:99fc121d491f46b38c49b8309f3bda06a695a3e9feff64951fea5b6c55be9f88"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:J3KQSGSVJ7NXT66GSP3JGQXNEL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","hep-ex","hep-ph","physics.data-an"],"primary_cat":"stat.ML","authors_text":"Antoine Wehenkel, Gilles Louppe, Maxime Vandegar, Michael Kagan","submitted_at":"2020-11-11T14:59:34Z","abstract_excerpt":"We revisit empirical Bayes in the absence of a tractable likelihood function, as is typical in scientific domains relying on computer simulations. We investigate how the empirical Bayesian can make use of neural density estimators first to use all noise-corrupted observations to estimate a prior or source distribution over uncorrupted samples, and then to perform single-observation posterior inference using the fitted source distribution. We propose an approach based on the direct maximization of the log-marginal likelihood of the observations, examining both biased and de-biased estimators, a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.05836","kind":"arxiv","version":2},"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/2011.05836/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":"2026-07-05T02:18:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gX1d8zYCIJOAFita58A2tQa3hhLz4vhQGtFGTDJ7jj8T7gopTDLDSlXT1qjlpZGpBjYSI9Kyau05WPwZWTr+Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T21:41:52.740421Z"},"content_sha256":"d5141f79ceb4e91c839e7bdcd0e1bdd29ecd7cff35e76ae3e8c2a23e615de872","schema_version":"1.0","event_id":"sha256:d5141f79ceb4e91c839e7bdcd0e1bdd29ecd7cff35e76ae3e8c2a23e615de872"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J3KQSGSVJ7NXT66GSP3JGQXNEL/bundle.json","state_url":"https://pith.science/pith/J3KQSGSVJ7NXT66GSP3JGQXNEL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J3KQSGSVJ7NXT66GSP3JGQXNEL/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":"2026-08-09T21:41:52Z","links":{"resolver":"https://pith.science/pith/J3KQSGSVJ7NXT66GSP3JGQXNEL","bundle":"https://pith.science/pith/J3KQSGSVJ7NXT66GSP3JGQXNEL/bundle.json","state":"https://pith.science/pith/J3KQSGSVJ7NXT66GSP3JGQXNEL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J3KQSGSVJ7NXT66GSP3JGQXNEL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:J3KQSGSVJ7NXT66GSP3JGQXNEL","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":"cf68ca628709ea17acb22b5304c822b3e03e138972b7834ec779a3cec8c9d4f1","cross_cats_sorted":["cs.LG","hep-ex","hep-ph","physics.data-an"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-11-11T14:59:34Z","title_canon_sha256":"7dd6745bd9877ce5a789a5d8f64bb750e8da14ac256b913ed407eb2008759a0b"},"schema_version":"1.0","source":{"id":"2011.05836","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.05836","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"arxiv_version","alias_value":"2011.05836v2","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.05836","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"pith_short_12","alias_value":"J3KQSGSVJ7NX","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"pith_short_16","alias_value":"J3KQSGSVJ7NXT66G","created_at":"2026-07-05T02:18:57Z"},{"alias_kind":"pith_short_8","alias_value":"J3KQSGSV","created_at":"2026-07-05T02:18:57Z"}],"graph_snapshots":[{"event_id":"sha256:d5141f79ceb4e91c839e7bdcd0e1bdd29ecd7cff35e76ae3e8c2a23e615de872","target":"graph","created_at":"2026-07-05T02:18:57Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2011.05836/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We revisit empirical Bayes in the absence of a tractable likelihood function, as is typical in scientific domains relying on computer simulations. We investigate how the empirical Bayesian can make use of neural density estimators first to use all noise-corrupted observations to estimate a prior or source distribution over uncorrupted samples, and then to perform single-observation posterior inference using the fitted source distribution. We propose an approach based on the direct maximization of the log-marginal likelihood of the observations, examining both biased and de-biased estimators, a","authors_text":"Antoine Wehenkel, Gilles Louppe, Maxime Vandegar, Michael Kagan","cross_cats":["cs.LG","hep-ex","hep-ph","physics.data-an"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-11-11T14:59:34Z","title":"Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.05836","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":"sha256:99fc121d491f46b38c49b8309f3bda06a695a3e9feff64951fea5b6c55be9f88","target":"record","created_at":"2026-07-05T02:18:57Z","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":"cf68ca628709ea17acb22b5304c822b3e03e138972b7834ec779a3cec8c9d4f1","cross_cats_sorted":["cs.LG","hep-ex","hep-ph","physics.data-an"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-11-11T14:59:34Z","title_canon_sha256":"7dd6745bd9877ce5a789a5d8f64bb750e8da14ac256b913ed407eb2008759a0b"},"schema_version":"1.0","source":{"id":"2011.05836","kind":"arxiv","version":2}},"canonical_sha256":"4ed5091a554fdb79fbc693f69342ed22e589b7ce72de2cd00c338840d73b8e53","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4ed5091a554fdb79fbc693f69342ed22e589b7ce72de2cd00c338840d73b8e53","first_computed_at":"2026-07-05T02:18:57.671685Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:18:57.671685Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kvnFUA9L9ccO3J9jJDMmPknGXXdDaww/7E1pWLSI66ZExzxB/38ML3eSl11t3VQZk9yPTRmyRsFQGk5X4QcyDw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:18:57.672152Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.05836","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:99fc121d491f46b38c49b8309f3bda06a695a3e9feff64951fea5b6c55be9f88","sha256:d5141f79ceb4e91c839e7bdcd0e1bdd29ecd7cff35e76ae3e8c2a23e615de872"],"state_sha256":"ae6c64370a1f1cc89bebd4d3968553aa8698b25be6904a634108d4c62055c270"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ysk3ugLm098wE3nSZ6zwpHqP4PmGkL/whTBR7tJd7XSYywErLh9XewtIP0ZYgqqC18rUSvLPWJatpgcSabkGDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T21:41:52.744483Z","bundle_sha256":"44ba23c3f3521319fee42376c4bb9854916506f69fcae789187a47187348f851"}}