Pith Number
pith:D5RLRK6X
pith:2019:D5RLRK6XUIDBUMVAYDRPD5U7XI
not attested
not anchored
not stored
refs pending
Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes
arxiv:1904.09370 v1 · 2019-04-19 · cs.LG · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{D5RLRK6XUIDBUMVAYDRPD5U7XI}
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 | 2026-05-17T23:43:49.526441Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
1f62b8abd7a2061a32a0c0e2f1f69fba0cda3d3df7bfe37d3f08ba7d0fcfd663
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/D5RLRK6XUIDBUMVAYDRPD5U7XI \
| 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: 1f62b8abd7a2061a32a0c0e2f1f69fba0cda3d3df7bfe37d3f08ba7d0fcfd663
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "5ea148032d2131d64e1e70db52dece2abe1221d94fe13cc2fbcca140aae6788a",
"cross_cats_sorted": [
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2019-04-19T23:28:11Z",
"title_canon_sha256": "8b0df8fe22cf1d1d223405d71ead4adcb951757df9191e40a1635d695abd7a12"
},
"schema_version": "1.0",
"source": {
"id": "1904.09370",
"kind": "arxiv",
"version": 1
}
}