{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:LCRRSTCHIRGOGRPKGQP7KSER7Z","short_pith_number":"pith:LCRRSTCH","schema_version":"1.0","canonical_sha256":"58a3194c47444ce345ea341ff54891fe6bc5955f5ac50644d335eec9a0f377e2","source":{"kind":"arxiv","id":"2507.02524","version":1},"attestation_state":"computed","paper":{"title":"Time Resolution Independent Operator Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NA","math.NA"],"primary_cat":"cs.CE","authors_text":"Diab W. Abueidda, Mbebo Nonna, Mostafa E. Mobasher, Panos Pantidis","submitted_at":"2025-07-03T10:44:57Z","abstract_excerpt":"Accurately learning solution operators for time-dependent partial differential equations (PDEs) from sparse and irregular data remains a challenging task. Recurrent DeepONet extensions inherit the discrete-time limitations of sequence-to-sequence (seq2seq) RNN architectures, while neural-ODE surrogates cannot incorporate new inputs after initialization. We introduce NCDE-DeepONet, a continuous-time operator network that embeds a Neural Controlled Differential Equation (NCDE) in the branch and augments the trunk with explicit space-time coordinates. The NCDE encodes an entire load history as th"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2507.02524","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2025-07-03T10:44:57Z","cross_cats_sorted":["cs.NA","math.NA"],"title_canon_sha256":"74325559bac838faf85c42ff05008a7a4041ef5f7238c640901a3b4ac3bb2210","abstract_canon_sha256":"ba10bc3717bc20308d0c49caa7057530a8a4a390c46523cee4e2ae85d7a3165d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:31:30.192769Z","signature_b64":"6XHSUMD4jRZaV0IZGdrtrYE09y6t4SyfIy5H+iPKq1gJVvpvhjnxUXrxLNVrUHrAHCVWR+de07p7ZxsDF0kzAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"58a3194c47444ce345ea341ff54891fe6bc5955f5ac50644d335eec9a0f377e2","last_reissued_at":"2026-07-05T11:31:30.192356Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:31:30.192356Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Time Resolution Independent Operator Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NA","math.NA"],"primary_cat":"cs.CE","authors_text":"Diab W. Abueidda, Mbebo Nonna, Mostafa E. Mobasher, Panos Pantidis","submitted_at":"2025-07-03T10:44:57Z","abstract_excerpt":"Accurately learning solution operators for time-dependent partial differential equations (PDEs) from sparse and irregular data remains a challenging task. Recurrent DeepONet extensions inherit the discrete-time limitations of sequence-to-sequence (seq2seq) RNN architectures, while neural-ODE surrogates cannot incorporate new inputs after initialization. We introduce NCDE-DeepONet, a continuous-time operator network that embeds a Neural Controlled Differential Equation (NCDE) in the branch and augments the trunk with explicit space-time coordinates. The NCDE encodes an entire load history as th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.02524","kind":"arxiv","version":1},"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/2507.02524/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2507.02524","created_at":"2026-07-05T11:31:30.192415+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.02524v1","created_at":"2026-07-05T11:31:30.192415+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.02524","created_at":"2026-07-05T11:31:30.192415+00:00"},{"alias_kind":"pith_short_12","alias_value":"LCRRSTCHIRGO","created_at":"2026-07-05T11:31:30.192415+00:00"},{"alias_kind":"pith_short_16","alias_value":"LCRRSTCHIRGOGRPK","created_at":"2026-07-05T11:31:30.192415+00:00"},{"alias_kind":"pith_short_8","alias_value":"LCRRSTCH","created_at":"2026-07-05T11:31:30.192415+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LCRRSTCHIRGOGRPKGQP7KSER7Z","json":"https://pith.science/pith/LCRRSTCHIRGOGRPKGQP7KSER7Z.json","graph_json":"https://pith.science/api/pith-number/LCRRSTCHIRGOGRPKGQP7KSER7Z/graph.json","events_json":"https://pith.science/api/pith-number/LCRRSTCHIRGOGRPKGQP7KSER7Z/events.json","paper":"https://pith.science/paper/LCRRSTCH"},"agent_actions":{"view_html":"https://pith.science/pith/LCRRSTCHIRGOGRPKGQP7KSER7Z","download_json":"https://pith.science/pith/LCRRSTCHIRGOGRPKGQP7KSER7Z.json","view_paper":"https://pith.science/paper/LCRRSTCH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.02524&json=true","fetch_graph":"https://pith.science/api/pith-number/LCRRSTCHIRGOGRPKGQP7KSER7Z/graph.json","fetch_events":"https://pith.science/api/pith-number/LCRRSTCHIRGOGRPKGQP7KSER7Z/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LCRRSTCHIRGOGRPKGQP7KSER7Z/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LCRRSTCHIRGOGRPKGQP7KSER7Z/action/storage_attestation","attest_author":"https://pith.science/pith/LCRRSTCHIRGOGRPKGQP7KSER7Z/action/author_attestation","sign_citation":"https://pith.science/pith/LCRRSTCHIRGOGRPKGQP7KSER7Z/action/citation_signature","submit_replication":"https://pith.science/pith/LCRRSTCHIRGOGRPKGQP7KSER7Z/action/replication_record"}},"created_at":"2026-07-05T11:31:30.192415+00:00","updated_at":"2026-07-05T11:31:30.192415+00:00"}