Pith Number
pith:OVZJ2P5I
pith:2017:OVZJ2P5I3D77WWGQLXKV4T3EAG
not attested
not anchored
not stored
refs pending
Deep Learning for Spatio-Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading
arxiv:1705.09851 v2 · 2017-05-27 · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{OVZJ2P5I3D77WWGQLXKV4T3EAG}
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 | 2026-05-18T00:16:45.309836Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
75729d3fa8d8fffb58d05dd55e4f6401be6b5abd8281e52d2373950fe669acaa
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OVZJ2P5I3D77WWGQLXKV4T3EAG \
| 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: 75729d3fa8d8fffb58d05dd55e4f6401be6b5abd8281e52d2373950fe669acaa
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "f24783d5b56b735d62b5dedf5f54b13a8ac39311dbccfe38d699ca1fb040f185",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.ML",
"submitted_at": "2017-05-27T18:17:58Z",
"title_canon_sha256": "ad0d398f3ce961cfbc7fa1cfc9f4856812ddbaebaaccb4ffc70c39d2bc5fa7ea"
},
"schema_version": "1.0",
"source": {
"id": "1705.09851",
"kind": "arxiv",
"version": 2
}
}