{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:SJ2CXVQNVXSIEHKGXJYP2XBYCD","short_pith_number":"pith:SJ2CXVQN","canonical_record":{"source":{"id":"2107.01214","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2021-07-02T18:00:03Z","cross_cats_sorted":["astro-ph.IM","cs.LG","hep-ph"],"title_canon_sha256":"b6aa17779eca4bb71baf89d71c1d4e8499a40bf327baf0b5b2d79a4a342d9320","abstract_canon_sha256":"9e515f42bebf301c514d4b68e2ff426f2036edfea814f3a1593371ab1270a0b0"},"schema_version":"1.0"},"canonical_sha256":"92742bd60dade4821d46ba70fd5c3810fabff8318122eab1aca636ea0c2697cf","source":{"kind":"arxiv","id":"2107.01214","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.01214","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"arxiv_version","alias_value":"2107.01214v2","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.01214","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"pith_short_12","alias_value":"SJ2CXVQNVXSI","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"pith_short_16","alias_value":"SJ2CXVQNVXSIEHKG","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"pith_short_8","alias_value":"SJ2CXVQN","created_at":"2026-07-05T03:25:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:SJ2CXVQNVXSIEHKGXJYP2XBYCD","target":"record","payload":{"canonical_record":{"source":{"id":"2107.01214","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2021-07-02T18:00:03Z","cross_cats_sorted":["astro-ph.IM","cs.LG","hep-ph"],"title_canon_sha256":"b6aa17779eca4bb71baf89d71c1d4e8499a40bf327baf0b5b2d79a4a342d9320","abstract_canon_sha256":"9e515f42bebf301c514d4b68e2ff426f2036edfea814f3a1593371ab1270a0b0"},"schema_version":"1.0"},"canonical_sha256":"92742bd60dade4821d46ba70fd5c3810fabff8318122eab1aca636ea0c2697cf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:25:32.904659Z","signature_b64":"gqm6yYhpeBf/Eb6irPTYgwNSjBwLVsyReZSsGcsGswIuU+kGlBjRInL7uqhs3tawYWUTqtilh5GP7q4vlQsACg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92742bd60dade4821d46ba70fd5c3810fabff8318122eab1aca636ea0c2697cf","last_reissued_at":"2026-07-05T03:25:32.904121Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:25:32.904121Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2107.01214","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":"2026-07-05T03:25:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a1niF+H8gsWPOKKHADNufIUcjvmGVirDPCxz+AS2HRhcLFSCZtdN7DUOzlhRfPB/3YmRSLXVE+uIXHjvMn3bAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T13:02:03.844946Z"},"content_sha256":"34503beea7c8ec7e100dca56a95171126e1b5e8d1e1993669687d9a3af583308","schema_version":"1.0","event_id":"sha256:34503beea7c8ec7e100dca56a95171126e1b5e8d1e1993669687d9a3af583308"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:SJ2CXVQNVXSIEHKGXJYP2XBYCD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Truncated Marginal Neural Ratio Estimation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG","hep-ph"],"primary_cat":"stat.ML","authors_text":"Alex Cole, Benjamin Kurt Miller, Christoph Weniger, Gilles Louppe, Patrick Forr\\'e","submitted_at":"2021-07-02T18:00:03Z","abstract_excerpt":"Parametric stochastic simulators are ubiquitous in science, often featuring high-dimensional input parameters and/or an intractable likelihood. Performing Bayesian parameter inference in this context can be challenging. We present a neural simulation-based inference algorithm which simultaneously offers simulation efficiency and fast empirical posterior testability, which is unique among modern algorithms. Our approach is simulation efficient by simultaneously estimating low-dimensional marginal posteriors instead of the joint posterior and by proposing simulations targeted to an observation o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.01214","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/2107.01214/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":"2026-07-05T03:25:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zgEI6xND6TofM+gexzucOrNgZ7i2Pct2nt1lP9iVIMTU6iEa6mzqg3IPU4/609ys3tut+k7eRqMMBtj2Q9hBAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T13:02:03.845744Z"},"content_sha256":"e1f72a3e1923264bf89cb5b99f54587275965368a29b08517f8fd5f6f53306b0","schema_version":"1.0","event_id":"sha256:e1f72a3e1923264bf89cb5b99f54587275965368a29b08517f8fd5f6f53306b0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SJ2CXVQNVXSIEHKGXJYP2XBYCD/bundle.json","state_url":"https://pith.science/pith/SJ2CXVQNVXSIEHKGXJYP2XBYCD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SJ2CXVQNVXSIEHKGXJYP2XBYCD/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":"2026-08-12T13:02:03Z","links":{"resolver":"https://pith.science/pith/SJ2CXVQNVXSIEHKGXJYP2XBYCD","bundle":"https://pith.science/pith/SJ2CXVQNVXSIEHKGXJYP2XBYCD/bundle.json","state":"https://pith.science/pith/SJ2CXVQNVXSIEHKGXJYP2XBYCD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SJ2CXVQNVXSIEHKGXJYP2XBYCD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:SJ2CXVQNVXSIEHKGXJYP2XBYCD","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":"9e515f42bebf301c514d4b68e2ff426f2036edfea814f3a1593371ab1270a0b0","cross_cats_sorted":["astro-ph.IM","cs.LG","hep-ph"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2021-07-02T18:00:03Z","title_canon_sha256":"b6aa17779eca4bb71baf89d71c1d4e8499a40bf327baf0b5b2d79a4a342d9320"},"schema_version":"1.0","source":{"id":"2107.01214","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.01214","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"arxiv_version","alias_value":"2107.01214v2","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.01214","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"pith_short_12","alias_value":"SJ2CXVQNVXSI","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"pith_short_16","alias_value":"SJ2CXVQNVXSIEHKG","created_at":"2026-07-05T03:25:32Z"},{"alias_kind":"pith_short_8","alias_value":"SJ2CXVQN","created_at":"2026-07-05T03:25:32Z"}],"graph_snapshots":[{"event_id":"sha256:e1f72a3e1923264bf89cb5b99f54587275965368a29b08517f8fd5f6f53306b0","target":"graph","created_at":"2026-07-05T03:25:32Z","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/2107.01214/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Parametric stochastic simulators are ubiquitous in science, often featuring high-dimensional input parameters and/or an intractable likelihood. Performing Bayesian parameter inference in this context can be challenging. We present a neural simulation-based inference algorithm which simultaneously offers simulation efficiency and fast empirical posterior testability, which is unique among modern algorithms. Our approach is simulation efficient by simultaneously estimating low-dimensional marginal posteriors instead of the joint posterior and by proposing simulations targeted to an observation o","authors_text":"Alex Cole, Benjamin Kurt Miller, Christoph Weniger, Gilles Louppe, Patrick Forr\\'e","cross_cats":["astro-ph.IM","cs.LG","hep-ph"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2021-07-02T18:00:03Z","title":"Truncated Marginal Neural Ratio Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.01214","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":"sha256:34503beea7c8ec7e100dca56a95171126e1b5e8d1e1993669687d9a3af583308","target":"record","created_at":"2026-07-05T03:25:32Z","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":"9e515f42bebf301c514d4b68e2ff426f2036edfea814f3a1593371ab1270a0b0","cross_cats_sorted":["astro-ph.IM","cs.LG","hep-ph"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2021-07-02T18:00:03Z","title_canon_sha256":"b6aa17779eca4bb71baf89d71c1d4e8499a40bf327baf0b5b2d79a4a342d9320"},"schema_version":"1.0","source":{"id":"2107.01214","kind":"arxiv","version":2}},"canonical_sha256":"92742bd60dade4821d46ba70fd5c3810fabff8318122eab1aca636ea0c2697cf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"92742bd60dade4821d46ba70fd5c3810fabff8318122eab1aca636ea0c2697cf","first_computed_at":"2026-07-05T03:25:32.904121Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:25:32.904121Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gqm6yYhpeBf/Eb6irPTYgwNSjBwLVsyReZSsGcsGswIuU+kGlBjRInL7uqhs3tawYWUTqtilh5GP7q4vlQsACg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:25:32.904659Z","signed_message":"canonical_sha256_bytes"},"source_id":"2107.01214","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:34503beea7c8ec7e100dca56a95171126e1b5e8d1e1993669687d9a3af583308","sha256:e1f72a3e1923264bf89cb5b99f54587275965368a29b08517f8fd5f6f53306b0"],"state_sha256":"adf869eab14bce055cf71f2170c5a857f5fc9ef2b941ddd3a2abcba3a6c42a81"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x8ze33o3mEMpmcBHod+IzV/eUZj8RrdyWgABoSROj3Qn0zdIfLAkcW3iKRuX5/2ggvnG3Paj0y52+6TeFZn+Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T13:02:03.851470Z","bundle_sha256":"2d1ade1e6071959f87b0ee089ed50d3eef99364d70fe750de39b86414ecb197a"}}