Pith Number
pith:SCBYUIDH
pith:2025:SCBYUIDHGIMXI3NLH72FEHFCVA
not attested
not anchored
not stored
refs pending
Can Bayesian Neural Networks Explicitly Model Input Uncertainty?
arxiv:2501.08285 v1 · 2025-01-14 · cs.LG · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{SCBYUIDHGIMXI3NLH72FEHFCVA}
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Record completeness
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Bitcoin timestamp
2
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4
Citations
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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
LUCAS-MEGA: A Large-Scale Multimodal Dataset for Representation Learning in Soil-Environment Systems
LUCAS-MEGA: A Large-Scale Multimodal Dataset for Representation Learning in Soil-Environment Systems
Receipt and verification
| First computed | 2026-07-05T10:00:58.760657Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
90838a20673219746dab3ff4521ca2a820f462df8fad795c7d7d1b552a050343
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/SCBYUIDHGIMXI3NLH72FEHFCVA \
| 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: 90838a20673219746dab3ff4521ca2a820f462df8fad795c7d7d1b552a050343
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "3837688b40abd22ff166ff2887358b09d5af51632b76df7730df4b1715fd2f4a",
"cross_cats_sorted": [
"cs.CV"
],
"license": "http://creativecommons.org/publicdomain/zero/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-01-14T18:00:41Z",
"title_canon_sha256": "00bda6b680d1be57577a80c836599f0c3da4e6b17c7ece7b9eed5928acfd1edc"
},
"schema_version": "1.0",
"source": {
"id": "2501.08285",
"kind": "arxiv",
"version": 1
}
}