{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:YDDYZNFMKBCJAXVGZFPABBUQ4T","short_pith_number":"pith:YDDYZNFM","canonical_record":{"source":{"id":"2406.13154","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-06-19T02:09:15Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"9221d09ae0603f2d955131c5e8b157308274e41fb4c58657ff8e1cf6a3289a76","abstract_canon_sha256":"223ea929b03a9cd4a2af7ac96892aad88e771fa9a8337ae62727588876bed431"},"schema_version":"1.0"},"canonical_sha256":"c0c78cb4ac5044905ea6c95e008690e4ef02e39314d0e510096c4210a854305e","source":{"kind":"arxiv","id":"2406.13154","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.13154","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"arxiv_version","alias_value":"2406.13154v3","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.13154","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"pith_short_12","alias_value":"YDDYZNFMKBCJ","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"pith_short_16","alias_value":"YDDYZNFMKBCJAXVG","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"pith_short_8","alias_value":"YDDYZNFM","created_at":"2026-07-05T09:26:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:YDDYZNFMKBCJAXVGZFPABBUQ4T","target":"record","payload":{"canonical_record":{"source":{"id":"2406.13154","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-06-19T02:09:15Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"9221d09ae0603f2d955131c5e8b157308274e41fb4c58657ff8e1cf6a3289a76","abstract_canon_sha256":"223ea929b03a9cd4a2af7ac96892aad88e771fa9a8337ae62727588876bed431"},"schema_version":"1.0"},"canonical_sha256":"c0c78cb4ac5044905ea6c95e008690e4ef02e39314d0e510096c4210a854305e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:26:28.507997Z","signature_b64":"S2Nck1Y8yZlGByhvshpW/0P43N/qtbsBoJxO+KBpd9gtdIjH7yQAUq2qXFA5cYhX5CaZH/ORpR2PBCGk9gNvCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c0c78cb4ac5044905ea6c95e008690e4ef02e39314d0e510096c4210a854305e","last_reissued_at":"2026-07-05T09:26:28.507536Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:26:28.507536Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.13154","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":"2026-07-05T09:26:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"toHcb7z89zumuZ7sHr1VmzttL7H9zVbDRvwtfwQo+nsH3lXjXeDxRFuOzOxt/dAAnouHAgFegcOGG+inVCS2AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T08:52:59.452337Z"},"content_sha256":"f24fe9b35aa195736ffbb90e6124c91f4f3d4d4d8e44942450fe1845610de145","schema_version":"1.0","event_id":"sha256:f24fe9b35aa195736ffbb90e6124c91f4f3d4d4d8e44942450fe1845610de145"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:YDDYZNFMKBCJAXVGZFPABBUQ4T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Conditional score-based diffusion models for solving inverse problems in mechanics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"stat.ML","authors_text":"Agnimitra Dasgupta, Assad Oberai, Brendan Kennedy, Harisankar Ramaswamy, Javier Murgoitio-Esandi, Ken Foo, Qifa Zhou, Runze Li","submitted_at":"2024-06-19T02:09:15Z","abstract_excerpt":"We propose a framework to perform Bayesian inference using conditional score-based diffusion models to solve a class of inverse problems in mechanics involving the inference of a specimen's spatially varying material properties from noisy measurements of its mechanical response to loading. Conditional score-based diffusion models are generative models that learn to approximate the score function of a conditional distribution using samples from the joint distribution. More specifically, the score functions corresponding to multiple realizations of the measurement are approximated using a single"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.13154","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/2406.13154/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":"2026-07-05T09:26:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tIJEGbjzaJka/2TKvl/GphmdJYknScFGCDm34Z67liJb0eRGSSOItG8pdqdbAdLckHFO6QDKMY4Ch74cuHuKAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T08:52:59.452828Z"},"content_sha256":"ac30c292d077d98b41f27683901d9d3ad8eb7062b3ce1031b8900cba575cbc97","schema_version":"1.0","event_id":"sha256:ac30c292d077d98b41f27683901d9d3ad8eb7062b3ce1031b8900cba575cbc97"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YDDYZNFMKBCJAXVGZFPABBUQ4T/bundle.json","state_url":"https://pith.science/pith/YDDYZNFMKBCJAXVGZFPABBUQ4T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YDDYZNFMKBCJAXVGZFPABBUQ4T/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":"2026-08-08T08:52:59Z","links":{"resolver":"https://pith.science/pith/YDDYZNFMKBCJAXVGZFPABBUQ4T","bundle":"https://pith.science/pith/YDDYZNFMKBCJAXVGZFPABBUQ4T/bundle.json","state":"https://pith.science/pith/YDDYZNFMKBCJAXVGZFPABBUQ4T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YDDYZNFMKBCJAXVGZFPABBUQ4T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YDDYZNFMKBCJAXVGZFPABBUQ4T","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":"223ea929b03a9cd4a2af7ac96892aad88e771fa9a8337ae62727588876bed431","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-06-19T02:09:15Z","title_canon_sha256":"9221d09ae0603f2d955131c5e8b157308274e41fb4c58657ff8e1cf6a3289a76"},"schema_version":"1.0","source":{"id":"2406.13154","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.13154","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"arxiv_version","alias_value":"2406.13154v3","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.13154","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"pith_short_12","alias_value":"YDDYZNFMKBCJ","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"pith_short_16","alias_value":"YDDYZNFMKBCJAXVG","created_at":"2026-07-05T09:26:28Z"},{"alias_kind":"pith_short_8","alias_value":"YDDYZNFM","created_at":"2026-07-05T09:26:28Z"}],"graph_snapshots":[{"event_id":"sha256:ac30c292d077d98b41f27683901d9d3ad8eb7062b3ce1031b8900cba575cbc97","target":"graph","created_at":"2026-07-05T09:26:28Z","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/2406.13154/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a framework to perform Bayesian inference using conditional score-based diffusion models to solve a class of inverse problems in mechanics involving the inference of a specimen's spatially varying material properties from noisy measurements of its mechanical response to loading. Conditional score-based diffusion models are generative models that learn to approximate the score function of a conditional distribution using samples from the joint distribution. More specifically, the score functions corresponding to multiple realizations of the measurement are approximated using a single","authors_text":"Agnimitra Dasgupta, Assad Oberai, Brendan Kennedy, Harisankar Ramaswamy, Javier Murgoitio-Esandi, Ken Foo, Qifa Zhou, Runze Li","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-06-19T02:09:15Z","title":"Conditional score-based diffusion models for solving inverse problems in mechanics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.13154","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:f24fe9b35aa195736ffbb90e6124c91f4f3d4d4d8e44942450fe1845610de145","target":"record","created_at":"2026-07-05T09:26:28Z","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":"223ea929b03a9cd4a2af7ac96892aad88e771fa9a8337ae62727588876bed431","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-06-19T02:09:15Z","title_canon_sha256":"9221d09ae0603f2d955131c5e8b157308274e41fb4c58657ff8e1cf6a3289a76"},"schema_version":"1.0","source":{"id":"2406.13154","kind":"arxiv","version":3}},"canonical_sha256":"c0c78cb4ac5044905ea6c95e008690e4ef02e39314d0e510096c4210a854305e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c0c78cb4ac5044905ea6c95e008690e4ef02e39314d0e510096c4210a854305e","first_computed_at":"2026-07-05T09:26:28.507536Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:26:28.507536Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"S2Nck1Y8yZlGByhvshpW/0P43N/qtbsBoJxO+KBpd9gtdIjH7yQAUq2qXFA5cYhX5CaZH/ORpR2PBCGk9gNvCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:26:28.507997Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.13154","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f24fe9b35aa195736ffbb90e6124c91f4f3d4d4d8e44942450fe1845610de145","sha256:ac30c292d077d98b41f27683901d9d3ad8eb7062b3ce1031b8900cba575cbc97"],"state_sha256":"d5268abf83f37e1ffb10e5f4694db6d03b46040f6f8998b3020a9e4b1cc26c53"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4nCIHXvkMZQMQs3JdIGs9Liunw3QYMfmJniQYhin6VgpRaqaMwr9qydE94PhXm2fMnBkijsQOvxBGBNXfPRcAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T08:52:59.456118Z","bundle_sha256":"7c417bede8a39cc0d8f422e1f3aadc5c52107446f0e8061b2d7eac9a204998d8"}}