{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OKXL2UOY6N2Q3NJANT4TTRPEBR","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":"f5dbe1ecedf6199362320a3d0d1bd3d0413e47296437858f193f81eedb12a555","cross_cats_sorted":["cs.AI","cs.CV","cs.NA","math.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-25T17:48:24Z","title_canon_sha256":"0ca6d00b617b0d6a9e0cfa25ed57ebd757dbd7366812f853cd56fa0ed1b9a837"},"schema_version":"1.0","source":{"id":"2406.17763","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.17763","created_at":"2026-07-05T09:29:30Z"},{"alias_kind":"arxiv_version","alias_value":"2406.17763v2","created_at":"2026-07-05T09:29:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.17763","created_at":"2026-07-05T09:29:30Z"},{"alias_kind":"pith_short_12","alias_value":"OKXL2UOY6N2Q","created_at":"2026-07-05T09:29:30Z"},{"alias_kind":"pith_short_16","alias_value":"OKXL2UOY6N2Q3NJA","created_at":"2026-07-05T09:29:30Z"},{"alias_kind":"pith_short_8","alias_value":"OKXL2UOY","created_at":"2026-07-05T09:29:30Z"}],"graph_snapshots":[{"event_id":"sha256:eb741c530c7334862c522d3e1a86f2816a9c22a9e6c5083b892ae34035da9a99","target":"graph","created_at":"2026-07-05T09:29:30Z","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/2406.17763/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce a general framework for solving partial differential equations (PDEs) using generative diffusion models. In particular, we focus on the scenarios where we do not have the full knowledge of the scene necessary to apply classical solvers. Most existing forward or inverse PDE approaches perform poorly when the observations on the data or the underlying coefficients are incomplete, which is a common assumption for real-world measurements. In this work, we propose DiffusionPDE that can simultaneously fill in the missing information and solve a PDE by modeling the joint distribution of ","authors_text":"Guandao Yang, Jeong Joon Park, Jiahe Huang, Zichen Wang","cross_cats":["cs.AI","cs.CV","cs.NA","math.NA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-25T17:48:24Z","title":"DiffusionPDE: Generative PDE-Solving Under Partial Observation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.17763","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:f3ffced64956a2d9ced4b70ca3e0468a4ea34a7e8dea51e52caaee1cc7cd6a9d","target":"record","created_at":"2026-07-05T09:29:30Z","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":"f5dbe1ecedf6199362320a3d0d1bd3d0413e47296437858f193f81eedb12a555","cross_cats_sorted":["cs.AI","cs.CV","cs.NA","math.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-25T17:48:24Z","title_canon_sha256":"0ca6d00b617b0d6a9e0cfa25ed57ebd757dbd7366812f853cd56fa0ed1b9a837"},"schema_version":"1.0","source":{"id":"2406.17763","kind":"arxiv","version":2}},"canonical_sha256":"72aebd51d8f3750db5206cf939c5e40c44d9d66a9c6d2a9037f7ee053ba8e100","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"72aebd51d8f3750db5206cf939c5e40c44d9d66a9c6d2a9037f7ee053ba8e100","first_computed_at":"2026-07-05T09:29:30.793037Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:29:30.793037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"es+fjTdmqnJT3GAatzbYCBcCgSlEegbgPuvjtMu5BzCczZeuoeDstU1vmrqjlU/xRQOOOIiy+Pu64v3FhddyDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:29:30.793542Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.17763","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f3ffced64956a2d9ced4b70ca3e0468a4ea34a7e8dea51e52caaee1cc7cd6a9d","sha256:eb741c530c7334862c522d3e1a86f2816a9c22a9e6c5083b892ae34035da9a99"],"state_sha256":"a28379831687e01106329152291304f5411a15cd75728c474ba75d7fcb2080a8"}