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Why does Deep Learning work? - A perspective from Group Theory
v1v2v3 (latest)

Why does Deep Learning work? - A perspective from Group Theory

20 December 2014
Arnab Paul
Suresh Venkatasubramanian
ArXiv (abs)PDFHTML

Papers citing "Why does Deep Learning work? - A perspective from Group Theory"

6 / 6 papers shown
Title
Deep Neural Networks are Easily Fooled: High Confidence Predictions for
  Unrecognizable Images
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
171
3,275
0
05 Dec 2014
An exact mapping between the Variational Renormalization Group and Deep
  Learning
An exact mapping between the Variational Renormalization Group and Deep Learning
Pankaj Mehta
D. Schwab
AI4CE
91
312
0
14 Oct 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
280
14,961
1
21 Dec 2013
Unsupervised Learning of Invariant Representations in Hierarchical
  Architectures
Unsupervised Learning of Invariant Representations in Hierarchical Architectures
Fabio Anselmi
Joel Z Leibo
Lorenzo Rosasco
Jim Mutch
Andrea Tacchetti
T. Poggio
OCL
78
88
0
17 Nov 2013
Deep Learning of Representations: Looking Forward
Deep Learning of Representations: Looking Forward
Yoshua Bengio
218
682
0
02 May 2013
Group Symmetry and Covariance Regularization
Group Symmetry and Covariance Regularization
P. Shah
V. Chandrasekaran
82
27
0
30 Nov 2011
1