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Deep learning for pedestrians: backpropagation in CNNs

Deep learning for pedestrians: backpropagation in CNNs

29 November 2018
L. Boué
    3DV
    PINN
ArXivPDFHTML

Papers citing "Deep learning for pedestrians: backpropagation in CNNs"

3 / 3 papers shown
Title
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
349
0
14 Jun 2018
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks
  and Visual Cortex
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex
Q. Liao
T. Poggio
213
255
0
13 Apr 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,156
0
06 Jun 2015
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