Pith Number
pith:J6F7SXXQ
pith:2015:J6F7SXXQOHBLT3MQL3542LE3NO
not attested
not anchored
not stored
refs pending
Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series
arxiv:1504.01575 v3 · 2015-04-07 · cs.LG · cs.NE
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{J6F7SXXQOHBLT3MQL3542LE3NO}
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 | 2026-05-18T01:28:14.417499Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4f8bf95ef071c2b9ed905efbcd2c9b6b945494531374b58813e720b898b4b70c
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/J6F7SXXQOHBLT3MQL3542LE3NO \
| 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: 4f8bf95ef071c2b9ed905efbcd2c9b6b945494531374b58813e720b898b4b70c
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "3764096b49ea42c662bd158208d61f9d00f29509c58db817ebfc696861179fb2",
"cross_cats_sorted": [
"cs.NE"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2015-04-07T12:21:03Z",
"title_canon_sha256": "a8e340556b2f8d461b845d6561d63627c0945e31d4c67917ce870288eb6c96f8"
},
"schema_version": "1.0",
"source": {
"id": "1504.01575",
"kind": "arxiv",
"version": 3
}
}