Pith Number
pith:LGJ2JBXZ
pith:2018:LGJ2JBXZUTBPBEMDHM5PY7JDMP
not attested
not anchored
not stored
refs pending
Robust training of recurrent neural networks to handle missing data for disease progression modeling
arxiv:1808.05500 v1 · 2018-08-16 · cs.CV · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{LGJ2JBXZUTBPBEMDHM5PY7JDMP}
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 | 2026-05-18T00:07:56.835775Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
5993a486f9a4c2f091833b3afc7d2363dad234b5d64e4e63acb9e11ea409a7f5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/LGJ2JBXZUTBPBEMDHM5PY7JDMP \
| 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: 5993a486f9a4c2f091833b3afc7d2363dad234b5d64e4e63acb9e11ea409a7f5
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "380883b2bd453d3d44bfada2a6cfaa3f7be966be0e9955832f87f8115571d257",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2018-08-16T14:09:22Z",
"title_canon_sha256": "e32d3b41c4937c5b2c1baaa39866d76b23859bb3898ba45ff50f1b80b5551506"
},
"schema_version": "1.0",
"source": {
"id": "1808.05500",
"kind": "arxiv",
"version": 1
}
}