{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:25ALMGVUYVU5REI5JC5KNHQ4AB","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":"69a665b52d05f87c5a8e54329d1d3f5a645daa842ec8ff5a780c8cebee4948cd","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-01-07T14:37:14Z","title_canon_sha256":"e58a2fac6e619480088ded2db025f909ccb33b5e2592a9ff723c1bc66748dcf3"},"schema_version":"1.0","source":{"id":"2501.03825","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.03825","created_at":"2026-07-05T09:58:00Z"},{"alias_kind":"arxiv_version","alias_value":"2501.03825v1","created_at":"2026-07-05T09:58:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.03825","created_at":"2026-07-05T09:58:00Z"},{"alias_kind":"pith_short_12","alias_value":"25ALMGVUYVU5","created_at":"2026-07-05T09:58:00Z"},{"alias_kind":"pith_short_16","alias_value":"25ALMGVUYVU5REI5","created_at":"2026-07-05T09:58:00Z"},{"alias_kind":"pith_short_8","alias_value":"25ALMGVU","created_at":"2026-07-05T09:58:00Z"}],"graph_snapshots":[{"event_id":"sha256:32f84c810b4823edea288381e6907968349bee56509113294b214915b348bd79","target":"graph","created_at":"2026-07-05T09:58:00Z","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/2501.03825/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Ultrasound images are commonly formed by sequential acquisition of beam-steered scan-lines. Minimizing the number of required scan-lines can significantly enhance frame rate, field of view, energy efficiency, and data transfer speeds. Existing approaches typically use static subsampling schemes in combination with sparsity-based or, more recently, deep-learning-based recovery. In this work, we introduce an adaptive subsampling method that maximizes intrinsic information gain in-situ, employing a Sylvester Normalizing Flow encoder to infer an approximate Bayesian posterior under partial observa","authors_text":"Hans van Gorp, Ruud J.G. van Sloun, Simon W. Penninga","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-01-07T14:37:14Z","title":"Deep Sylvester Posterior Inference for Adaptive Compressed Sensing in Ultrasound Imaging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.03825","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":"sha256:647e8f88ea51ab3d80b47fd9114f755590c3df0e57c72fbc3c5feccd45fa3557","target":"record","created_at":"2026-07-05T09:58:00Z","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":"69a665b52d05f87c5a8e54329d1d3f5a645daa842ec8ff5a780c8cebee4948cd","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-01-07T14:37:14Z","title_canon_sha256":"e58a2fac6e619480088ded2db025f909ccb33b5e2592a9ff723c1bc66748dcf3"},"schema_version":"1.0","source":{"id":"2501.03825","kind":"arxiv","version":1}},"canonical_sha256":"d740b61ab4c569d8911d48baa69e1c004aa7f6c7dd754058e91890086e6572a6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d740b61ab4c569d8911d48baa69e1c004aa7f6c7dd754058e91890086e6572a6","first_computed_at":"2026-07-05T09:58:00.117347Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:58:00.117347Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4QIUuykrzHxD6isUpOzHXZs+QplQeZbtfEQRmv5ZTUg6xf7C/awhPRHtKS2MFkh5BjuXtD463OoJF8dq0q5PAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:58:00.117870Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.03825","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:647e8f88ea51ab3d80b47fd9114f755590c3df0e57c72fbc3c5feccd45fa3557","sha256:32f84c810b4823edea288381e6907968349bee56509113294b214915b348bd79"],"state_sha256":"6a3654becb07740bc574bc68aa588051fa05f9463dfc559e8031bf9300cb40f6"}