Pith Number
pith:QBNHPNR7
pith:2018:QBNHPNR7MF6SL7FLDXUJ4LJE5Q
not attested
not anchored
not stored
refs pending
Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?
arxiv:1810.09102 v1 · 2018-10-22 · cs.LG · cs.CV · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{QBNHPNR7MF6SL7FLDXUJ4LJE5Q}
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
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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 | 2026-05-18T00:02:41.017094Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
805a77b63f617d25fcab1de89e2d24ec315db77428826530071110c9ced4aa06
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QBNHPNR7MF6SL7FLDXUJ4LJE5Q \
| 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: 805a77b63f617d25fcab1de89e2d24ec315db77428826530071110c9ced4aa06
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "b1fbc103653db86e6f7be5b00a444f248414d558bdf9f9fbc332849e8fdacb55",
"cross_cats_sorted": [
"cs.CV",
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2018-10-22T06:22:54Z",
"title_canon_sha256": "aa6ce3a874892108ef2632057eae9ac19618f42d096645672553946c9f2bd115"
},
"schema_version": "1.0",
"source": {
"id": "1810.09102",
"kind": "arxiv",
"version": 1
}
}