Pith Number

pith:7S3JU73E

pith:2026:7S3JU73EF46KIT3MIHZI7EBYNF

not attested not anchored not stored refs pending

Bayesian Rain Field Reconstruction using Commercial Microwave Links and Diffusion Model Priors

Albina Ilina, Badr Moufad, Eric Moulines, Hagit Messer, Hai Victor Habi, Salem Lahlou, Yazid Janati

Diffusion models as priors in a Bayesian inverse problem improve rainfall field reconstruction from commercial microwave link measurements.

arxiv:2605.05520 v2 · 2026-05-06 · cs.LG · stat.AP · stat.ML

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{7S3JU73EF46KIT3MIHZI7EBYNF}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Experiments on synthetic and real-world datasets demonstrate consistent improvements over established CML-based reconstruction baselines.

C2weakest 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.

C3one 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.

Receipt and verification

First computed	2026-06-01T01:02:41.656360Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

fcb69a7f642f3ca44f6c41f28f9038695f00a3f64b0446a6073b791bae702e93

Aliases

arxiv: 2605.05520 · arxiv_version: 2605.05520v2 · doi: 10.48550/arxiv.2605.05520 · pith_short_12: 7S3JU73EF46K · pith_short_16: 7S3JU73EF46KIT3M · pith_short_8: 7S3JU73E

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/7S3JU73EF46KIT3MIHZI7EBYNF \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: fcb69a7f642f3ca44f6c41f28f9038695f00a3f64b0446a6073b791bae702e93

Canonical record JSON

{
  "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
  }
}