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Deep Networks with Stochastic Depth

Deep Networks with Stochastic Depth

30 March 2016
Gao Huang
Yu Sun
Zhuang Liu
Daniel Sedra
Kilian Q. Weinberger
ArXivPDFHTML

Papers citing "Deep Networks with Stochastic Depth"

27 / 477 papers shown
Title
ShaResNet: reducing residual network parameter number by sharing weights
ShaResNet: reducing residual network parameter number by sharing weights
Alexandre Boulch
29
26
0
28 Feb 2017
A Novel Weight-Shared Multi-Stage CNN for Scale Robustness
A Novel Weight-Shared Multi-Stage CNN for Scale Robustness
Ryo Takahashi
Takashi Matsubara
K. Uehara
OOD
30
21
0
12 Feb 2017
Feedback Networks
Feedback Networks
Amir Zamir
Te-Lin Wu
Lin Sun
Bokui (William) Shen
Jitendra Malik
Silvio Savarese
18
209
0
30 Dec 2016
Highway and Residual Networks learn Unrolled Iterative Estimation
Highway and Residual Networks learn Unrolled Iterative Estimation
Klaus Greff
R. Srivastava
Jürgen Schmidhuber
AI4TS
26
214
0
22 Dec 2016
Deep Pyramidal Residual Networks with Separated Stochastic Depth
Deep Pyramidal Residual Networks with Separated Stochastic Depth
Yoshihiro Yamada
Masakazu Iwamura
K. Kise
17
27
0
05 Dec 2016
PolyNet: A Pursuit of Structural Diversity in Very Deep Networks
PolyNet: A Pursuit of Structural Diversity in Very Deep Networks
Xingcheng Zhang
Zhizhong Li
Chen Change Loy
Dahua Lin
MDE
32
259
0
17 Nov 2016
Factorized Bilinear Models for Image Recognition
Factorized Bilinear Models for Image Recognition
Yanghao Li
Naiyan Wang
Jiaying Liu
Xiaodi Hou
19
96
0
17 Nov 2016
Regularizing CNNs with Locally Constrained Decorrelations
Regularizing CNNs with Locally Constrained Decorrelations
Pau Rodríguez López
Jordi Gonzalez
Guillem Cucurull
J. M. Gonfaus
F. X. Roca
35
133
0
07 Nov 2016
UMDFaces: An Annotated Face Dataset for Training Deep Networks
UMDFaces: An Annotated Face Dataset for Training Deep Networks
Ankan Bansal
Anirudh Nanduri
Carlos D. Castillo
Rajeev Ranjan
Rama Chellappa
CVBM
3DH
36
213
0
04 Nov 2016
Temporal Ensembling for Semi-Supervised Learning
Temporal Ensembling for Semi-Supervised Learning
S. Laine
Timo Aila
UQCV
25
2,523
0
07 Oct 2016
HyperNetworks
HyperNetworks
David R Ha
Andrew M. Dai
Quoc V. Le
84
1,585
0
27 Sep 2016
Making Deep Neural Networks Robust to Label Noise: a Loss Correction
  Approach
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach
Giorgio Patrini
A. Rozza
A. Menon
Richard Nock
Lizhen Qu
NoLa
51
1,435
0
13 Sep 2016
Hierarchical Multiscale Recurrent Neural Networks
Hierarchical Multiscale Recurrent Neural Networks
Junyoung Chung
Sungjin Ahn
Yoshua Bengio
BDL
29
534
0
06 Sep 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
L. V. D. van der Maaten
Kilian Q. Weinberger
PINN
3DV
315
36,381
0
25 Aug 2016
Lets keep it simple, Using simple architectures to outperform deeper and
  more complex architectures
Lets keep it simple, Using simple architectures to outperform deeper and more complex architectures
S. H. HasanPour
Mohammad Rouhani
Mohsen Fayyaz
Mohammad Sabokrou
18
118
0
22 Aug 2016
Mollifying Networks
Mollifying Networks
Çağlar Gülçehre
Marcin Moczulski
Francesco Visin
Yoshua Bengio
23
46
0
17 Aug 2016
Generative and Discriminative Voxel Modeling with Convolutional Neural
  Networks
Generative and Discriminative Voxel Modeling with Convolutional Neural Networks
Andrew Brock
Theodore Lim
J. Ritchie
Nick Weston
26
577
0
15 Aug 2016
Residual Networks of Residual Networks: Multilevel Residual Networks
Residual Networks of Residual Networks: Multilevel Residual Networks
Ke Zhang
Miao Sun
T. Han
Xingfang Yuan
Liru Guo
Tao Liu
18
303
0
09 Aug 2016
Group Sparse Regularization for Deep Neural Networks
Group Sparse Regularization for Deep Neural Networks
Simone Scardapane
Danilo Comminiello
Amir Hussain
A. Uncini
22
462
0
02 Jul 2016
Gaussian Error Linear Units (GELUs)
Gaussian Error Linear Units (GELUs)
Dan Hendrycks
Kevin Gimpel
81
4,873
0
27 Jun 2016
Convolutional Residual Memory Networks
Convolutional Residual Memory Networks
Joel Ruben Antony Moniz
C. Pal
28
23
0
16 Jun 2016
ENet: A Deep Neural Network Architecture for Real-Time Semantic
  Segmentation
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Adam Paszke
Abhishek Chaurasia
Sangpil Kim
Eugenio Culurciello
SSeg
235
2,056
0
07 Jun 2016
Density estimation using Real NVP
Density estimation using Real NVP
Falong Shen
Jascha Sohl-Dickstein
Gang Zeng
DRL
27
3,647
0
27 May 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
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
68
7,907
0
23 May 2016
Swapout: Learning an ensemble of deep architectures
Swapout: Learning an ensemble of deep architectures
Saurabh Singh
Derek Hoiem
David A. Forsyth
BDL
3DPC
OOD
UQCV
21
150
0
20 May 2016
Residual Networks Behave Like Ensembles of Relatively Shallow Networks
Residual Networks Behave Like Ensembles of Relatively Shallow Networks
Andreas Veit
Michael J. Wilber
Serge J. Belongie
UQCV
22
107
0
20 May 2016
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