Pith Number

pith:6J4VU6N2

pith:2026:6J4VU6N24QEF57VG4DB6Z74KE5

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Plug-In Classification of Drift Functions in Diffusion Processes Using Neural Networks

Jiarong Fan, Yating Liu, Yuzhen Zhao

A plug-in classifier estimates class-specific drift functions of diffusion processes with neural networks to achieve explicit convergence rates for excess misclassification risk.

arxiv:2602.02791 v2 · 2026-02-02 · stat.ML · cs.LG · math.ST · stat.TH

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Claims

C1strongest claim

Under standard regularity assumptions, we establish convergence rates for the excess misclassification risk, making explicit the contributions of drift estimation, time discretization, and dimension. Our analysis also highlights the benefit of exploiting the diffusion structure: the drift is learned from all observed increments, leading to sharper guarantees than direct trajectory-based neural classifiers.

C2weakest assumption

Standard regularity assumptions on the diffusion processes, drift functions, and neural network approximation capabilities hold, together with the requirement that drift functions admit a compositional structure for effective performance in higher dimensions.

C3one line summary

A neural-network plug-in classifier for multiclass diffusion processes achieves explicit convergence rates for excess misclassification risk by estimating class-specific drifts from discrete increments.

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-18T02:45:05.544893Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

f2795a79bae4085efea6e0c3ecff8a276a20811fa5fbbefbad70a0542db0d7a1

Aliases

arxiv: 2602.02791 · arxiv_version: 2602.02791v2 · doi: 10.48550/arxiv.2602.02791 · pith_short_12: 6J4VU6N24QEF · pith_short_16: 6J4VU6N24QEF57VG · pith_short_8: 6J4VU6N2

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/6J4VU6N24QEF57VG4DB6Z74KE5 \
  | 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: f2795a79bae4085efea6e0c3ecff8a276a20811fa5fbbefbad70a0542db0d7a1

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "c0c4e4803124211f6c518515a69011501c67228d7e79706f497c1c532b2f09fc",
    "cross_cats_sorted": [
      "cs.LG",
      "math.ST",
      "stat.TH"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "stat.ML",
    "submitted_at": "2026-02-02T20:48:01Z",
    "title_canon_sha256": "7972fb25870d1249c989c2ad726962f30e911c62825b2ea066e245d995267b27"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2602.02791",
    "kind": "arxiv",
    "version": 2
  }
}