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Dynamical Isometry and a Mean Field Theory of CNNs: How to Train
  10,000-Layer Vanilla Convolutional Neural Networks

Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks

14 June 2018
Lechao Xiao
Yasaman Bahri
Jascha Narain Sohl-Dickstein
S. Schoenholz
Jeffrey Pennington
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Papers citing "Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks"

2 / 2 papers shown
Title
Don't be lazy: CompleteP enables compute-efficient deep transformers
Don't be lazy: CompleteP enables compute-efficient deep transformers
Nolan Dey
Bin Claire Zhang
Lorenzo Noci
Mufan Bill Li
Blake Bordelon
Shane Bergsma
C. Pehlevan
Boris Hanin
Joel Hestness
4
0
0
02 May 2025
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification
Yoon Kim
AILaw
VLM
222
12,850
0
25 Aug 2014
1