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Densely Connected Convolutional Networks

Densely Connected Convolutional Networks

25 August 2016
Gao Huang
Zhuang Liu
L. V. D. van der Maaten
Kilian Q. Weinberger
    PINN
    3DV
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Papers citing "Densely Connected Convolutional Networks"

12 / 5,112 papers shown
Title
RetiNet: Automatic AMD identification in OCT volumetric data
RetiNet: Automatic AMD identification in OCT volumetric data
S. Apostolopoulos
Carlos Ciller
Sandro De Zanet
Sebastian Wolf
Raphael Sznitman
16
34
0
12 Oct 2016
Deep Learning Assessment of Tumor Proliferation in Breast Cancer
  Histological Images
Deep Learning Assessment of Tumor Proliferation in Breast Cancer Histological Images
Manan A. Shah
Christopher A. Rubadue
D. Suster
Dayong Wang
16
40
0
11 Oct 2016
HyperNetworks
HyperNetworks
David R Ha
Andrew M. Dai
Quoc V. Le
64
1,580
0
27 Sep 2016
Input Convex Neural Networks
Input Convex Neural Networks
Brandon Amos
Lei Xu
J. Zico Kolter
187
599
0
22 Sep 2016
Neural Photo Editing with Introspective Adversarial Networks
Neural Photo Editing with Introspective Adversarial Networks
Andrew Brock
Theodore Lim
J. Ritchie
Nick Weston
GAN
27
457
0
22 Sep 2016
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
Corinna Cortes
X. Gonzalvo
Vitaly Kuznetsov
M. Mohri
Scott Yang
29
282
0
05 Jul 2016
Supervised learning based on temporal coding in spiking neural networks
Supervised learning based on temporal coding in spiking neural networks
Hesham Mostafa
24
349
0
27 Jun 2016
FractalNet: Ultra-Deep Neural Networks without Residuals
FractalNet: Ultra-Deep Neural Networks without Residuals
Gustav Larsson
Michael Maire
Gregory Shakhnarovich
45
933
0
24 May 2016
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
Weight Normalization: A Simple Reparameterization to Accelerate Training
  of Deep Neural Networks
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
Tim Salimans
Diederik P. Kingma
ODL
66
1,924
0
25 Feb 2016
Improved graph-based SFA: Information preservation complements the
  slowness principle
Improved graph-based SFA: Information preservation complements the slowness principle
Alberto N. Escalante
Laurenz Wiskott
9
16
0
15 Jan 2016
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
34
43,009
0
11 Feb 2015
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