{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:7OB2CI272A2BD3TAVOZURJY3I2","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":"0b0575079c1ceae4ef0dd4fe2747453b1cb02b61bf9a42b6f51eb93f439aa686","cross_cats_sorted":["math.FA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.CA","submitted_at":"2017-02-13T16:21:22Z","title_canon_sha256":"400861b6ab76897f908bdf858b85ee97a25eb35ce87447b8f7d0ae8f20039be0"},"schema_version":"1.0","source":{"id":"1702.08497","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.08497","created_at":"2026-05-18T00:46:24Z"},{"alias_kind":"arxiv_version","alias_value":"1702.08497v2","created_at":"2026-05-18T00:46:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.08497","created_at":"2026-05-18T00:46:24Z"},{"alias_kind":"pith_short_12","alias_value":"7OB2CI272A2B","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_16","alias_value":"7OB2CI272A2BD3TA","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_8","alias_value":"7OB2CI27","created_at":"2026-05-18T12:31:05Z"}],"graph_snapshots":[{"event_id":"sha256:23059acb335370c2e43a63200f45d84b8c188d6b292ced5af291f9c5518d6833","target":"graph","created_at":"2026-05-18T00:46:24Z","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"},"paper":{"abstract_excerpt":"Standard interpolation techniques are implicitly based on the assumption that the signal lies on a homogeneous domain. In this letter, the proposed interpolation method instead exploits prior information about domain inhomogeneity, characterized by different, potentially overlapping, subdomains. By introducing a domain-similarity metric for each sample, the interpolation process is then based on a domain-informed consistency principle. We illustrate and demonstrate the feasibility of domain-informed linear interpolation in 1D, and also, on a real fMRI image in 2D. The results show the benefit ","authors_text":"Dimitri Van De Ville, Hamid Behjat, Leif S\\\"ornmo, Zafer Do\\u{g}an","cross_cats":["math.FA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.CA","submitted_at":"2017-02-13T16:21:22Z","title":"Interpolation in the Presence of Domain Inhomogeneity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.08497","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":"sha256:539c1258ab7f3887abe82ab1d6b41c51e144e833a920978a5e5c6af12ed286c4","target":"record","created_at":"2026-05-18T00:46:24Z","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":"0b0575079c1ceae4ef0dd4fe2747453b1cb02b61bf9a42b6f51eb93f439aa686","cross_cats_sorted":["math.FA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.CA","submitted_at":"2017-02-13T16:21:22Z","title_canon_sha256":"400861b6ab76897f908bdf858b85ee97a25eb35ce87447b8f7d0ae8f20039be0"},"schema_version":"1.0","source":{"id":"1702.08497","kind":"arxiv","version":2}},"canonical_sha256":"fb83a1235fd03411ee60abb348a71b46951dd8b5583bf1b304db2c5d7c78e179","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fb83a1235fd03411ee60abb348a71b46951dd8b5583bf1b304db2c5d7c78e179","first_computed_at":"2026-05-18T00:46:24.912087Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:46:24.912087Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V/GCeIwxdn16pUjQx8wB7oWSiBacdSbs97zjzw6Ss53dFM07/e9YiLGWqxhB1HfDnbw/etbFsYCTAzHaQGt8Bg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:46:24.912613Z","signed_message":"canonical_sha256_bytes"},"source_id":"1702.08497","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:539c1258ab7f3887abe82ab1d6b41c51e144e833a920978a5e5c6af12ed286c4","sha256:23059acb335370c2e43a63200f45d84b8c188d6b292ced5af291f9c5518d6833"],"state_sha256":"c6dc1799e4c81fc7a6ba2c95e33cba2c87e6443f4ab720b82442020c40ddf8a1"}