Pith Number
pith:LDYBZTHV
pith:2019:LDYBZTHVJ62ZDOQ2VDYQ7MDGNY
not attested
not anchored
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refs pending
A deep learning approach to real-time parking occupancy prediction in spatio-temporal networks incorporating multiple spatio-temporal data sources
arxiv:1901.06758 v5 · 2019-01-21 · cs.LG · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{LDYBZTHVJ62ZDOQ2VDYQ7MDGNY}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more
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 | 2026-05-17T23:46:29.135177Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
58f01cccf54fb591ba1aa8f10fb0666e032407e0f3ade011e873e6742bfb66f5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/LDYBZTHVJ62ZDOQ2VDYQ7MDGNY \
| 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: 58f01cccf54fb591ba1aa8f10fb0666e032407e0f3ade011e873e6742bfb66f5
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "7f2d5996a4b665a75f14d228b24245874115a7548c93003f1075ee14898363ca",
"cross_cats_sorted": [
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2019-01-21T01:20:27Z",
"title_canon_sha256": "8d22543eb05bc5fff9cf652d277f924523d1f34013b8a4a5c17fe9b4801f8e8d"
},
"schema_version": "1.0",
"source": {
"id": "1901.06758",
"kind": "arxiv",
"version": 5
}
}