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On the effect of the activation function on the distribution of hidden
  nodes in a deep network

On the effect of the activation function on the distribution of hidden nodes in a deep network

7 January 2019
Philip M. Long
Hanie Sedghi
ArXivPDFHTML

Papers citing "On the effect of the activation function on the distribution of hidden nodes in a deep network"

2 / 2 papers shown
Title
Bayesian Deep Convolutional Networks with Many Channels are Gaussian
  Processes
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Roman Novak
Lechao Xiao
Jaehoon Lee
Yasaman Bahri
Greg Yang
Jiri Hron
Daniel A. Abolafia
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCV
BDL
25
307
0
11 Oct 2018
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
Lechao Xiao
Yasaman Bahri
Jascha Narain Sohl-Dickstein
S. Schoenholz
Jeffrey Pennington
244
350
0
14 Jun 2018
1