{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:7KCN4P2K7UGXUJTLAOEOP5XRCJ","short_pith_number":"pith:7KCN4P2K","canonical_record":{"source":{"id":"2406.14292","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.CO","submitted_at":"2024-06-20T13:16:41Z","cross_cats_sorted":["math.OC","stat.ML"],"title_canon_sha256":"3b88ab16652cd9906b714c267f0d6f3e99702436dc3d83be9723788ed0a9e6ad","abstract_canon_sha256":"098cf96559b125ecebc7049b04f50f4a0454fdba51e7b5ea852918aae638f0ac"},"schema_version":"1.0"},"canonical_sha256":"fa84de3f4afd0d7a266b0388e7f6f11263ea8f989ce8f10473158d41b188862f","source":{"kind":"arxiv","id":"2406.14292","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.14292","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"arxiv_version","alias_value":"2406.14292v3","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.14292","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"pith_short_12","alias_value":"7KCN4P2K7UGX","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"pith_short_16","alias_value":"7KCN4P2K7UGXUJTL","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"pith_short_8","alias_value":"7KCN4P2K","created_at":"2026-07-05T11:11:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:7KCN4P2K7UGXUJTLAOEOP5XRCJ","target":"record","payload":{"canonical_record":{"source":{"id":"2406.14292","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.CO","submitted_at":"2024-06-20T13:16:41Z","cross_cats_sorted":["math.OC","stat.ML"],"title_canon_sha256":"3b88ab16652cd9906b714c267f0d6f3e99702436dc3d83be9723788ed0a9e6ad","abstract_canon_sha256":"098cf96559b125ecebc7049b04f50f4a0454fdba51e7b5ea852918aae638f0ac"},"schema_version":"1.0"},"canonical_sha256":"fa84de3f4afd0d7a266b0388e7f6f11263ea8f989ce8f10473158d41b188862f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:11:32.907677Z","signature_b64":"lQgeS+KhSt4Esv6L826pSg/Z3imWVv++1RZkmcdGuyt4kQQypxC2FqiC9hKDPzb28TkFdz+0cZ9+76NmjwRcAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa84de3f4afd0d7a266b0388e7f6f11263ea8f989ce8f10473158d41b188862f","last_reissued_at":"2026-07-05T11:11:32.907129Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:11:32.907129Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.14292","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":"2026-07-05T11:11:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lb4xmJWPrmr9CzXHJQ1Z953PnjeHh57TwZ6zcCKcxGsyl3lNQ5be+NBvKeulWzEqw70li1gsAJsT25bkEO4vDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T09:26:27.476517Z"},"content_sha256":"bb8c1112101d435c2c571a8000e8f4a47dca4b33a42b39d38fce7dd0624a2a7e","schema_version":"1.0","event_id":"sha256:bb8c1112101d435c2c571a8000e8f4a47dca4b33a42b39d38fce7dd0624a2a7e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:7KCN4P2K7UGXUJTLAOEOP5XRCJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Proximal Interacting Particle Langevin Algorithms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC","stat.ML"],"primary_cat":"stat.CO","authors_text":"Francesca R. Crucinio, O. Deniz Akyildiz, Paula Cordero Encinar","submitted_at":"2024-06-20T13:16:41Z","abstract_excerpt":"We introduce a class of algorithms, termed proximal interacting particle Langevin algorithms (PIPLA), for inference and learning in latent variable models whose joint probability density is non-differentiable. Leveraging proximal Markov chain Monte Carlo techniques and interacting particle Langevin algorithms, we propose three algorithms tailored to the problem of estimating parameters in a non-differentiable statistical model. We prove nonasymptotic bounds for the parameter estimates produced by the different algorithms in the strongly log-concave setting and provide comprehensive numerical e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.14292","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/2406.14292/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":"2026-07-05T11:11:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"voBSxvwSWpyfxax+ihOLQ1aXcJURKYvUlwtmCrZngr/vlZYMLPj9uFlIyk3maPW2HO6xswIiZ5iLB5ipGuYDAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T09:26:27.477042Z"},"content_sha256":"8e2c3273ab73dd7449e9c383768bc97391a8e9cc40904c4e3c818ebc38463671","schema_version":"1.0","event_id":"sha256:8e2c3273ab73dd7449e9c383768bc97391a8e9cc40904c4e3c818ebc38463671"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7KCN4P2K7UGXUJTLAOEOP5XRCJ/bundle.json","state_url":"https://pith.science/pith/7KCN4P2K7UGXUJTLAOEOP5XRCJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7KCN4P2K7UGXUJTLAOEOP5XRCJ/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":"2026-08-13T09:26:27Z","links":{"resolver":"https://pith.science/pith/7KCN4P2K7UGXUJTLAOEOP5XRCJ","bundle":"https://pith.science/pith/7KCN4P2K7UGXUJTLAOEOP5XRCJ/bundle.json","state":"https://pith.science/pith/7KCN4P2K7UGXUJTLAOEOP5XRCJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7KCN4P2K7UGXUJTLAOEOP5XRCJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7KCN4P2K7UGXUJTLAOEOP5XRCJ","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":"098cf96559b125ecebc7049b04f50f4a0454fdba51e7b5ea852918aae638f0ac","cross_cats_sorted":["math.OC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.CO","submitted_at":"2024-06-20T13:16:41Z","title_canon_sha256":"3b88ab16652cd9906b714c267f0d6f3e99702436dc3d83be9723788ed0a9e6ad"},"schema_version":"1.0","source":{"id":"2406.14292","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.14292","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"arxiv_version","alias_value":"2406.14292v3","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.14292","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"pith_short_12","alias_value":"7KCN4P2K7UGX","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"pith_short_16","alias_value":"7KCN4P2K7UGXUJTL","created_at":"2026-07-05T11:11:32Z"},{"alias_kind":"pith_short_8","alias_value":"7KCN4P2K","created_at":"2026-07-05T11:11:32Z"}],"graph_snapshots":[{"event_id":"sha256:8e2c3273ab73dd7449e9c383768bc97391a8e9cc40904c4e3c818ebc38463671","target":"graph","created_at":"2026-07-05T11:11:32Z","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/2406.14292/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce a class of algorithms, termed proximal interacting particle Langevin algorithms (PIPLA), for inference and learning in latent variable models whose joint probability density is non-differentiable. Leveraging proximal Markov chain Monte Carlo techniques and interacting particle Langevin algorithms, we propose three algorithms tailored to the problem of estimating parameters in a non-differentiable statistical model. We prove nonasymptotic bounds for the parameter estimates produced by the different algorithms in the strongly log-concave setting and provide comprehensive numerical e","authors_text":"Francesca R. Crucinio, O. Deniz Akyildiz, Paula Cordero Encinar","cross_cats":["math.OC","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.CO","submitted_at":"2024-06-20T13:16:41Z","title":"Proximal Interacting Particle Langevin Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.14292","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:bb8c1112101d435c2c571a8000e8f4a47dca4b33a42b39d38fce7dd0624a2a7e","target":"record","created_at":"2026-07-05T11:11:32Z","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":"098cf96559b125ecebc7049b04f50f4a0454fdba51e7b5ea852918aae638f0ac","cross_cats_sorted":["math.OC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.CO","submitted_at":"2024-06-20T13:16:41Z","title_canon_sha256":"3b88ab16652cd9906b714c267f0d6f3e99702436dc3d83be9723788ed0a9e6ad"},"schema_version":"1.0","source":{"id":"2406.14292","kind":"arxiv","version":3}},"canonical_sha256":"fa84de3f4afd0d7a266b0388e7f6f11263ea8f989ce8f10473158d41b188862f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa84de3f4afd0d7a266b0388e7f6f11263ea8f989ce8f10473158d41b188862f","first_computed_at":"2026-07-05T11:11:32.907129Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:11:32.907129Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lQgeS+KhSt4Esv6L826pSg/Z3imWVv++1RZkmcdGuyt4kQQypxC2FqiC9hKDPzb28TkFdz+0cZ9+76NmjwRcAw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:11:32.907677Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.14292","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb8c1112101d435c2c571a8000e8f4a47dca4b33a42b39d38fce7dd0624a2a7e","sha256:8e2c3273ab73dd7449e9c383768bc97391a8e9cc40904c4e3c818ebc38463671"],"state_sha256":"7c25ea2025831ebdf1ec71151476e3242507db465f8429e519a9e51606cb6ac0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EA3VKTl+GOlh2xBHJHz2GUUhNIyC+1uZkCFB/LK43nbB9D3K1S98s2Gfx/c/LoRUZmZPNU3FzXGPyMsmcKrECg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T09:26:27.481423Z","bundle_sha256":"99407aefcecb957ad4d8bad7874178fd32a2bcf11aff03f4a5d420ea15ad37f6"}}