{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:KPHLQXDCK2S3TEJN3EDLS6IZFN","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":"9a9d66585b9202b1bea5c252f9680b8ea15ed3abf3096168ce93495f5f4d4f52","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-15T19:24:14Z","title_canon_sha256":"bf25633dc166517374d66eba3459f996764b6d82c6ed4c37a943229b31ca45e1"},"schema_version":"1.0","source":{"id":"2303.08891","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.08891","created_at":"2026-07-05T05:51:46Z"},{"alias_kind":"arxiv_version","alias_value":"2303.08891v1","created_at":"2026-07-05T05:51:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.08891","created_at":"2026-07-05T05:51:46Z"},{"alias_kind":"pith_short_12","alias_value":"KPHLQXDCK2S3","created_at":"2026-07-05T05:51:46Z"},{"alias_kind":"pith_short_16","alias_value":"KPHLQXDCK2S3TEJN","created_at":"2026-07-05T05:51:46Z"},{"alias_kind":"pith_short_8","alias_value":"KPHLQXDC","created_at":"2026-07-05T05:51:46Z"}],"graph_snapshots":[{"event_id":"sha256:3f35088160108c17fdbf9f3b580bf2c09c871bce33b02b5d73a77b31d50cb104","target":"graph","created_at":"2026-07-05T05:51:46Z","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/2303.08891/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We combine vision transformers with operator learning to solve diverse inverse problems described by partial differential equations (PDEs). Our approach, named ViTO, combines a U-Net based architecture with a vision transformer. We apply ViTO to solve inverse PDE problems of increasing complexity, namely for the wave equation, the Navier-Stokes equations and the Darcy equation. We focus on the more challenging case of super-resolution, where the input dataset for the inverse problem is at a significantly coarser resolution than the output. The results we obtain are comparable or exceed the lea","authors_text":"Adar Kahana, Eli Turkel, George Em Karniadakis, Oded Ovadia, Panos Stinis","cross_cats":["cs.NA","math.NA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-15T19:24:14Z","title":"ViTO: Vision Transformer-Operator"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.08891","kind":"arxiv","version":1},"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":"sha256:0030c1c84cf4d42bdd4054702cee9a879a30ea0e40584c66c21cff63737bb79a","target":"record","created_at":"2026-07-05T05:51:46Z","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":"9a9d66585b9202b1bea5c252f9680b8ea15ed3abf3096168ce93495f5f4d4f52","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-15T19:24:14Z","title_canon_sha256":"bf25633dc166517374d66eba3459f996764b6d82c6ed4c37a943229b31ca45e1"},"schema_version":"1.0","source":{"id":"2303.08891","kind":"arxiv","version":1}},"canonical_sha256":"53ceb85c6256a5b9912dd906b979192b541fa6664460fd3f6757b9d90f40c88e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"53ceb85c6256a5b9912dd906b979192b541fa6664460fd3f6757b9d90f40c88e","first_computed_at":"2026-07-05T05:51:46.632807Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:51:46.632807Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jcZ8Y0eF2VlBymU/kRKIadqJeMcd5FjZLmCQQD4ucY0OpB18a1teLJQ/4yZLpBanfjcWb3uNdy+6lV7MZ90EDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:51:46.633161Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.08891","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0030c1c84cf4d42bdd4054702cee9a879a30ea0e40584c66c21cff63737bb79a","sha256:3f35088160108c17fdbf9f3b580bf2c09c871bce33b02b5d73a77b31d50cb104"],"state_sha256":"790a1e9c888031bcd858e9594abf6b83ecc01d155398fc5d0bbfa06e14f61f8e"}