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pith:3VKFXRQM

pith:2026:3VKFXRQM6RXARY7J43WUMGYQRO
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A Theory of Saddle Escape in Deep Nonlinear Networks

Divit Rawal, Michael R. DeWeese

An exact identity on Frobenius norm imbalances in layer weights reduces deep nonlinear training to a scalar ODE whose escape time scales as ε to the power of minus (r minus 2), where r is the number of bottleneck layers.

arxiv:2605.01288 v3 · 2026-05-02 · cs.LG · cond-mat.dis-nn · stat.ML

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Record completeness

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3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

We derive an exact identity for the imbalance of Frobenius norms of layer weight matrices that holds for any smooth activation and any differentiable loss [...] giving a critical-depth escape time law τ★ = Θ(ε^{-(r-2)}) governed by the number r of layers at the bottleneck scale rather than the total depth L.

C2weakest assumption

The reduction to a scalar ODE relies on an approximate balance law on the permutation-symmetric submanifold whose accuracy and range of validity are not derived from first principles but stated as holding approximately.

C3one line summary

An exact norm-imbalance identity classifies activations into four classes and reduces deep nonlinear training flow to a scalar ODE that predicts saddle escape time scaling as ε to the power of minus (r-2) for r bottleneck layers.

Formal links

2 machine-checked theorem links

Receipt and verification
First computed 2026-06-24T01:15:03.268859Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

dd545bc60cf46e08e3e9e6ed461b108b829581fa3e9cacc5ccac9f69c012f4bf

Aliases

arxiv: 2605.01288 · arxiv_version: 2605.01288v3 · doi: 10.48550/arxiv.2605.01288 · pith_short_12: 3VKFXRQM6RXA · pith_short_16: 3VKFXRQM6RXARY7J · pith_short_8: 3VKFXRQM
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3VKFXRQM6RXARY7J43WUMGYQRO \
  | 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: dd545bc60cf46e08e3e9e6ed461b108b829581fa3e9cacc5ccac9f69c012f4bf
Canonical record JSON
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    "cross_cats_sorted": [
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      "stat.ML"
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-02T06:55:15Z",
    "title_canon_sha256": "52163603e99629cbdd0bb6cb17146be35167df9f9963c970d5f3e49cf163a903"
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