Pith Number
pith:NJLB2RQD
pith:2025:NJLB2RQDFRJXUVKDM4VJIKVVIW
not attested
not anchored
not stored
refs pending
Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection
arxiv:2503.11255 v1 · 2025-03-14 · cs.LG · cs.DC
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{NJLB2RQDFRJXUVKDM4VJIKVVIW}
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
· sign in to
claim
4
Citations
5
Replications
✓
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T10:31:15.534615Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6a561d46032c537a5543672a942ab545ba3c11105b1498be358a60c21b03efdf
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NJLB2RQDFRJXUVKDM4VJIKVVIW \
| 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: 6a561d46032c537a5543672a942ab545ba3c11105b1498be358a60c21b03efdf
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "9ad50f0cb692d532e6ff73b79156d9865d3de4a552ad205f419a8f7828f38933",
"cross_cats_sorted": [
"cs.DC"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-03-14T10:06:52Z",
"title_canon_sha256": "a3d3665317e689217045b46970d9c9a36c0497331669d1a26bb70093cc9b1ad2"
},
"schema_version": "1.0",
"source": {
"id": "2503.11255",
"kind": "arxiv",
"version": 1
}
}