Pith Number
pith:AZH6YPET
pith:2019:AZH6YPETEMX54JYHCDC7SUEYWK
not attested
not anchored
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refs pending
Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks
arxiv:1906.00150 v5 · 2019-06-01 · cs.LG · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{AZH6YPETEMX54JYHCDC7SUEYWK}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T00:38:45.285357Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
064fec3c93232fde270710c5f95098b2ae21e906c06dc82d46fe11defaac4f8f
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/AZH6YPETEMX54JYHCDC7SUEYWK \
| 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: 064fec3c93232fde270710c5f95098b2ae21e906c06dc82d46fe11defaac4f8f
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "220cfe2a769d115f5a71a71879d14633db7c8eb62dca3eea2b80bdecfb007f6b",
"cross_cats_sorted": [
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2019-06-01T04:03:53Z",
"title_canon_sha256": "c97f67547020fac18f4ac11458aee93a73a950de8d8985b90a1c7be391976575"
},
"schema_version": "1.0",
"source": {
"id": "1906.00150",
"kind": "arxiv",
"version": 5
}
}