Pith Number
pith:YEBJHSTM
pith:2019:YEBJHSTMEGVUJPH32PX2VEVRNW
not attested
not anchored
not stored
refs pending
Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness
arxiv:1906.01444 v1 · 2019-06-02 · cs.CR · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{YEBJHSTMEGVUJPH32PX2VEVRNW}
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
· sign in to
claim
4
Citations
5
Replications
✓
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 | 2026-05-17T23:44:16.585670Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c10293ca6c21ab44bcfbd3efaa92b16db199c7ca7561300089b6110bc14605b5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YEBJHSTMEGVUJPH32PX2VEVRNW \
| 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: c10293ca6c21ab44bcfbd3efaa92b16db199c7ca7561300089b6110bc14605b5
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "507ac88030379692dde039f461bab13b163e6b996e95f7f5bdf62ac06218637a",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CR",
"submitted_at": "2019-06-02T18:20:36Z",
"title_canon_sha256": "d17e623250d7d68d4f3ef27f44b7b383505f33fd0c061e16e2906e8d2b390146"
},
"schema_version": "1.0",
"source": {
"id": "1906.01444",
"kind": "arxiv",
"version": 1
}
}