Pith Number
pith:M7FUUZN6
pith:2017:M7FUUZN6EPT33VB35NZUMHPMWD
not attested
not anchored
not stored
refs pending
Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations
arxiv:1706.04702 v1 · 2017-06-15 · math.NA · cs.LG · cs.NA · cs.NE · math.PR · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{M7FUUZN6EPT33VB35NZUMHPMWD}
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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 | 2026-06-04T18:10:55.716557Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
67cb4a65be23e7bdd43beb73461decb0db255ba4af1498da23365cbe52544ced
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/M7FUUZN6EPT33VB35NZUMHPMWD \
| 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: 67cb4a65be23e7bdd43beb73461decb0db255ba4af1498da23365cbe52544ced
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "53cf5b40ff30ef0dd4d37144d7d215e373eb8b1b55e05a6f293c921ed3c47b90",
"cross_cats_sorted": [
"cs.LG",
"cs.NA",
"cs.NE",
"math.PR",
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "math.NA",
"submitted_at": "2017-06-15T00:28:58Z",
"title_canon_sha256": "0bbca4ab30e2c138aaf3c75cf3419f1b0826556fbf7b0f0f25f69bd5da35471d"
},
"schema_version": "1.0",
"source": {
"id": "1706.04702",
"kind": "arxiv",
"version": 1
}
}