Pith Number
pith:IFNCSUDQ
pith:2018:IFNCSUDQWJUMYUTOSZWNSPHHGY
not attested
not anchored
not stored
refs pending
Weakly-Supervised Deep Learning of Heat Transport via Physics Informed Loss
arxiv:1807.11374 v2 · 2018-07-24 · stat.ML · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{IFNCSUDQWJUMYUTOSZWNSPHHGY}
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
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claim
4
Citations
5
Replications
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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.
Receipt and verification
| First computed | 2026-05-18T00:07:32.299637Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
415a295070b268cc526e966cd93ce7363825a573cc69a95626d9f930f349a046
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IFNCSUDQWJUMYUTOSZWNSPHHGY \
| 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: 415a295070b268cc526e966cd93ce7363825a573cc69a95626d9f930f349a046
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "ce9b2f66172e49e4eb393bde5a44155387a2c784c185f1b363143a5159d7a61c",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.ML",
"submitted_at": "2018-07-24T17:58:56Z",
"title_canon_sha256": "9658ad72b5b6ecece074f69fd6f4fce945b4edf224178f64c9a9d9ba14336159"
},
"schema_version": "1.0",
"source": {
"id": "1807.11374",
"kind": "arxiv",
"version": 2
}
}