Pith Number
pith:ZZLPML3K
pith:2020:ZZLPML3KR32JCTI2PKOCWU4DIE
not attested
not anchored
not stored
refs pending
Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
arxiv:2005.07427 v2 · 2020-05-15 · cs.LG · cs.SI · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{ZZLPML3KR32JCTI2PKOCWU4DIE}
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
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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.
Cited by
Receipt and verification
| First computed | 2026-07-05T01:05:27.499420Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
ce56f62f6a8ef4914d1a7a9c2b538341235ee9745f71f50f6e77a0f8e578c3b7
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ZZLPML3KR32JCTI2PKOCWU4DIE \
| 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: ce56f62f6a8ef4914d1a7a9c2b538341235ee9745f71f50f6e77a0f8e578c3b7
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "107731726da4af2ed32ca53ff1f41efc036f2ffd64559b7447e357b03cfc8abc",
"cross_cats_sorted": [
"cs.SI",
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2020-05-15T09:17:08Z",
"title_canon_sha256": "f9f6e02255b628f8f9ae6bc1546e73d3becee5e15eab65ef37c40a35e7abfea7"
},
"schema_version": "1.0",
"source": {
"id": "2005.07427",
"kind": "arxiv",
"version": 2
}
}