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We show that diffusion models better preserve key rainfall statistics compa","authors_text":"Albina Ilina, Badr Moufad, Eric Moulines, Hagit Messer, Hai Victor Habi, Salem Lahlou, Yazid Janati","cross_cats":["stat.AP","stat.ML"],"headline":"Diffusion models as priors in a Bayesian inverse problem improve rainfall field reconstruction from commercial microwave link measurements.","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-06T23:36:46Z","title":"Bayesian Rain Field Reconstruction using Commercial Microwave Links and Diffusion Model Priors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.05520","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-08T16:20:36.312900Z","id":"9e630683-851c-496d-b8bd-1c893fc61f80","model_set":{"reader":"grok-4.3"},"one_line_summary":"Diffusion model priors enable training-free Bayesian sampling for more accurate rain field reconstruction from path-integrated commercial microwave link measurements than Gaussian process baselines.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Diffusion models as priors in a Bayesian inverse problem improve rainfall field reconstruction from commercial microwave link measurements.","strongest_claim":"Experiments on synthetic and real-world datasets demonstrate consistent improvements over established CML-based reconstruction baselines.","weakest_assumption":"That pre-trained diffusion models, without domain-specific adaptation, provide high-fidelity priors that accurately capture rainfall spatial statistics and that the forward model of line-integrated attenuation is sufficiently accurate for heterogeneous precipitation."}},"verdict_id":"9e630683-851c-496d-b8bd-1c893fc61f80"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:62f634cbd4a15825bd5938eaa4fde8cc20b36c710d637f3436e5753b20d5c5a0","target":"record","created_at":"2026-06-01T01:02:41Z","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":"908ed3a53a559a1c66f6f11fa48dc11180572e65f772d7afa135c07c2f05bfed","cross_cats_sorted":["stat.AP","stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-06T23:36:46Z","title_canon_sha256":"d77415a122f42ca79c1cd0b8144820e34b8c08947d3938947216e12d6f51c73f"},"schema_version":"1.0","source":{"id":"2605.05520","kind":"arxiv","version":2}},"canonical_sha256":"fcb69a7f642f3ca44f6c41f28f9038695f00a3f64b0446a6073b791bae702e93","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fcb69a7f642f3ca44f6c41f28f9038695f00a3f64b0446a6073b791bae702e93","first_computed_at":"2026-06-01T01:02:41.656360Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:02:41.656360Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bEg90nBMi5L/sgFy0PCn4eADAMBeVjhlq//5ikgGXnZO73blK3EvPjG/eVnhm/0Ohaji2citC6ycL7ymy8dIBQ==","signature_status":"signed_v1","signed_at":"2026-06-01T01:02:41.657302Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.05520","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fe6cb5424536d80b4844c94eb5121f3ba9be503e3998cf9dbe23f71c81e857e5","sha256:62f634cbd4a15825bd5938eaa4fde8cc20b36c710d637f3436e5753b20d5c5a0","sha256:5dd65c5a40d017462964c27223587c52543cfdc4d2c1e8288d7b6e7d4d1e54f7"],"state_sha256":"cfff6999ed2eebbefd59f9b517698e4020faffabc3fc315c351e2d006b7a57be"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3ZQapui00kF0kGCUA6PQlzayq5yJ8EObR36dsEkzUtrn/VfQEqp3RSaEkQ6KeujFB9+Yk6WldPFsp1/oNhGLDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T23:18:38.196790Z","bundle_sha256":"e93d591dccc38160bea42877e8f3c27140073783ee7979b49d77fc36afdd19b5"}}