Pith Number
pith:ZVKZESOQ
pith:2019:ZVKZESOQ5M4JZCG2YEX5R5E5VN
not attested
not anchored
not stored
refs pending
DSTP-RNN: a dual-stage two-phase attention-based recurrent neural networks for long-term and multivariate time series prediction
arxiv:1904.07464 v1 · 2019-04-16 · cs.LG · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{ZVKZESOQ5M4JZCG2YEX5R5E5VN}
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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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 | 2026-05-17T23:48:25.167506Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
cd559249d0eb389c88dac12fd8f49dab49c1d1a5a97f774f78080e884a98850c
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ZVKZESOQ5M4JZCG2YEX5R5E5VN \
| 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: cd559249d0eb389c88dac12fd8f49dab49c1d1a5a97f774f78080e884a98850c
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "740be6e719f286219562c921260fd18c9b3da04a60cd2c851f13ae3d5ccff62a",
"cross_cats_sorted": [
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2019-04-16T05:03:45Z",
"title_canon_sha256": "45bca2b1fb9316f6049bf722dc6f3a8e7d54c4380abb60ae70ee6022f993bcfb"
},
"schema_version": "1.0",
"source": {
"id": "1904.07464",
"kind": "arxiv",
"version": 1
}
}