Pith Number
pith:D7LHXMRR
pith:2022:D7LHXMRR3QKFGXPWCNVZ3H337B
not attested
not anchored
not stored
refs pending
Learning Large Causal Structures from Inverse Covariance Matrix via Sparse Matrix Decomposition
arxiv:2211.14221 v3 · 2022-11-25 · cs.LG · math.OC · stat.ME
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{D7LHXMRR3QKFGXPWCNVZ3H337B}
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
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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 | 2026-07-05T07:47:00.107082Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
1fd67bb231dc14535df6136b9d9f7bf849d591f0a79c38ea66d9f585168c821c
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/D7LHXMRR3QKFGXPWCNVZ3H337B \
| 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: 1fd67bb231dc14535df6136b9d9f7bf849d591f0a79c38ea66d9f585168c821c
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "da2615a6421c0fc9ea5b7dc382faa8882418a578379bb914f841f0366fadd970",
"cross_cats_sorted": [
"math.OC",
"stat.ME"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2022-11-25T16:32:56Z",
"title_canon_sha256": "3ce908163059834cedbbb31ca400125021b3109f7877f8e2168cc55a3c0ae667"
},
"schema_version": "1.0",
"source": {
"id": "2211.14221",
"kind": "arxiv",
"version": 3
}
}