Pith Number
pith:BSCGEISO
pith:2022:BSCGEISOSQ2IPYFN47TOA5Z374
not attested
not anchored
not stored
refs pending
Beyond the Quadratic Approximation: the Multiscale Structure of Neural Network Loss Landscapes
arxiv:2204.11326 v3 · 2022-04-24 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{BSCGEISOSQ2IPYFN47TOA5Z374}
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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.
Cited by
Understanding Quantization-Aware Training: Gradients at Quantized Weights Bias to the Low-Loss Basin
Receipt and verification
| First computed | 2026-07-05T04:34:04.415152Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
0c8462224e943487e0ade7e6e0773bff3c9b83bc67185c4e5f6ecdb72d437d47
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/BSCGEISOSQ2IPYFN47TOA5Z374 \
| 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: 0c8462224e943487e0ade7e6e0773bff3c9b83bc67185c4e5f6ecdb72d437d47
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "e59ae543c839fb863d66be1eedb2ad2de676b1e2796a9e2066b8f2386c2eccb2",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2022-04-24T17:34:12Z",
"title_canon_sha256": "3710aaf3bd53515b73e61896df8e204fb69bbdd10db00517d19cc78970a31617"
},
"schema_version": "1.0",
"source": {
"id": "2204.11326",
"kind": "arxiv",
"version": 3
}
}