Pith Number
pith:JQW6YHJ4
pith:2026:JQW6YHJ4ZHQM2YPBVYS5COL2EB
not attested
not anchored
not stored
refs pending
A Bayesian Filtering Approach for Learning Lagrangian Dynamics from Noisy Measurements
arxiv:2606.31137 v1 · 2026-06-30 · cs.LG · eess.SP
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JQW6YHJ4ZHQM2YPBVYS5COL2EB}
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
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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 | 2026-07-01T01:17:30.244005Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4c2dec1d3cc9e0cd61e1ae25d1397a204b77984b9d91a9cb4c8735b4a88ccee8
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JQW6YHJ4ZHQM2YPBVYS5COL2EB \
| 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: 4c2dec1d3cc9e0cd61e1ae25d1397a204b77984b9d91a9cb4c8735b4a88ccee8
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "5cd9a7524e31c6ed354f2fff261d55eebccee0a8a75b87f004dca642d6767b6d",
"cross_cats_sorted": [
"eess.SP"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2026-06-30T05:07:57Z",
"title_canon_sha256": "7a6d218ca67cb1c8346e2e1c0b4485ac8cdfa862e6957d6059857d0cfcd31ceb"
},
"schema_version": "1.0",
"source": {
"id": "2606.31137",
"kind": "arxiv",
"version": 1
}
}