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Striving for Simplicity: The All Convolutional Net
v1v2v3 (latest)

Striving for Simplicity: The All Convolutional Net

21 December 2014
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
    FAtt
ArXiv (abs)PDFHTML

Papers citing "Striving for Simplicity: The All Convolutional Net"

50 / 1,866 papers shown
Title
Hierarchical interpretations for neural network predictions
Hierarchical interpretations for neural network predictions
Chandan Singh
W. James Murdoch
Bin Yu
84
146
0
14 Jun 2018
Early Seizure Detection with an Energy-Efficient Convolutional Neural
  Network on an Implantable Microcontroller
Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller
Maria Hügle
S. Heller
Manuel Watter
Manuel Blum
F. Manzouri
M. Dümpelmann
A. Schulze-Bonhage
P. Woias
Joschka Boedecker
48
43
0
12 Jun 2018
Understanding Patch-Based Learning by Explaining Predictions
Understanding Patch-Based Learning by Explaining Predictions
Christopher J. Anders
G. Montavon
Wojciech Samek
K. Müller
UQCVFAtt
62
6
0
11 Jun 2018
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image
  Segmentation Pipelines
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines
Martin Rajchl
Nick Pawlowski
Daniel Rueckert
Paul M. Matthews
Ben Glocker
SSeg
69
35
0
11 Jun 2018
A Note about: Local Explanation Methods for Deep Neural Networks lack
  Sensitivity to Parameter Values
A Note about: Local Explanation Methods for Deep Neural Networks lack Sensitivity to Parameter Values
Mukund Sundararajan
Ankur Taly
FAtt
46
21
0
11 Jun 2018
Data augmentation instead of explicit regularization
Data augmentation instead of explicit regularization
Alex Hernández-García
Peter König
111
144
0
11 Jun 2018
Quantitative Phase Imaging and Artificial Intelligence: A Review
Quantitative Phase Imaging and Artificial Intelligence: A Review
YoungJu Jo
Hyungjoon Cho
Sang Yun Lee
Gunho Choi
Geon Kim
Hyun-Seok Min
Yongkeun Park
100
155
0
06 Jun 2018
Rethinking Radiology: An Analysis of Different Approaches to BraTS
Rethinking Radiology: An Analysis of Different Approaches to BraTS
William Bakst
Linus Meyer-Teruel
Jasdeep Singh
28
2
0
06 Jun 2018
Spatial Frequency Loss for Learning Convolutional Autoencoders
Spatial Frequency Loss for Learning Convolutional Autoencoders
N. Ichimura
31
9
0
06 Jun 2018
EIGEN: Ecologically-Inspired GENetic Approach for Neural Network
  Structure Searching from Scratch
EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching from Scratch
Jian Ren
Zhe Li
Jianchao Yang
N. Xu
Tianbao Yang
D. Foran
78
17
0
05 Jun 2018
Backdrop: Stochastic Backpropagation
Backdrop: Stochastic Backpropagation
Siavash Golkar
Kyle Cranmer
50
2
0
04 Jun 2018
Differential Diagnosis for Pancreatic Cysts in CT Scans Using
  Densely-Connected Convolutional Networks
Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks
Hongwei Bran Li
Kanru Lin
M. Reichert
Lina Xu
R. Braren
D. Fu
R. Schmid
Ji Li
Bjoern Menze
Kuangyu Shi
MedIm
38
29
0
04 Jun 2018
Disconnected Manifold Learning for Generative Adversarial Networks
Disconnected Manifold Learning for Generative Adversarial Networks
Mahyar Khayatkhoei
Ahmed Elgammal
Maneesh Kumar Singh
GAN
95
77
0
03 Jun 2018
IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural
  Networks
IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks
Ke Sun
Mingjie Li
Dong Liu
Jingdong Wang
124
126
0
01 Jun 2018
Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations
Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations
Guannan Zhao
Bo Zhou
Kaiwen Wang
Rui Jiang
Min Xu
FAttMedIm
71
48
0
31 May 2018
Defending Against Machine Learning Model Stealing Attacks Using
  Deceptive Perturbations
Defending Against Machine Learning Model Stealing Attacks Using Deceptive Perturbations
Taesung Lee
Ben Edwards
Ian Molloy
D. Su
AAML
134
41
0
31 May 2018
How Important Is a Neuron?
How Important Is a Neuron?
Kedar Dhamdhere
Mukund Sundararajan
Qiqi Yan
FAttGNN
77
131
0
30 May 2018
Rice Classification Using Spatio-Spectral Deep Convolutional Neural
  Network
Rice Classification Using Spatio-Spectral Deep Convolutional Neural Network
I. Chatnuntawech
Kittipong Tantisantisom
P. Khanchaitit
T. Boonkoom
B. Bilgiç
Ekapol Chuangsuwanich
32
26
0
29 May 2018
Lightweight Probabilistic Deep Networks
Lightweight Probabilistic Deep Networks
Jochen Gast
Stefan Roth
UQCVOODBDL
93
183
0
29 May 2018
Video Anomaly Detection and Localization via Gaussian Mixture Fully
  Convolutional Variational Autoencoder
Video Anomaly Detection and Localization via Gaussian Mixture Fully Convolutional Variational Autoencoder
Yaxiang Fan
G. Wen
Deren Li
S. Qiu
M. Levine
DRL
68
213
0
29 May 2018
Object-Oriented Dynamics Predictor
Object-Oriented Dynamics Predictor
Guangxiang Zhu
Zhiao Huang
Chongjie Zhang
AI4CE
89
35
0
25 May 2018
Semantic Network Interpretation
Semantic Network Interpretation
Pei Guo
Ryan Farrell
MILMFAtt
34
0
0
23 May 2018
Classifier-agnostic saliency map extraction
Classifier-agnostic saliency map extraction
Konrad Zolna
Krzysztof J. Geras
Kyunghyun Cho
78
29
0
21 May 2018
Wavelet Convolutional Neural Networks
Wavelet Convolutional Neural Networks
S. Fujieda
Kohei Takayama
T. Hachisuka
68
129
0
20 May 2018
Sampling-Free Variational Inference of Bayesian Neural Networks by
  Variance Backpropagation
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation
Manuel Haussmann
Fred Hamprecht
M. Kandemir
BDL
72
6
0
19 May 2018
Dynamic learning rate using Mutual Information
Dynamic learning rate using Mutual Information
Shrihari Vasudevan
21
6
0
18 May 2018
A Theoretical Explanation for Perplexing Behaviors of
  Backpropagation-based Visualizations
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations
Weili Nie
Yang Zhang
Ankit B. Patel
FAtt
179
151
0
18 May 2018
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class
  Models
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models
Jacob R. Kauffmann
K. Müller
G. Montavon
DRL
77
98
0
16 May 2018
Did the Model Understand the Question?
Did the Model Understand the Question?
Pramod Kaushik Mudrakarta
Ankur Taly
Mukund Sundararajan
Kedar Dhamdhere
ELMOODFAtt
85
199
0
14 May 2018
Energy Efficient Hadamard Neural Networks
Energy Efficient Hadamard Neural Networks
T. C. Deveci
Serdar Çakır
A. Enis Cetin
49
18
0
14 May 2018
Adaptive Selection of Deep Learning Models on Embedded Systems
Adaptive Selection of Deep Learning Models on Embedded Systems
Ben Taylor
Vicent Sanz Marco
W. Wolff
Yehia El-khatib
Zheng Wang
36
13
0
11 May 2018
Robust Classification with Convolutional Prototype Learning
Robust Classification with Convolutional Prototype Learning
Hong-Ming Yang
Xu-Yao Zhang
Fei Yin
Cheng-Lin Liu
69
346
0
09 May 2018
Visual Global Localization with a Hybrid WNN-CNN Approach
Visual Global Localization with a Hybrid WNN-CNN Approach
Avelino Forechi
Thiago Oliveira-Santos
C. Badue
Alberto F. de Souza
34
7
0
08 May 2018
N2RPP: An Adversarial Network to Rebuild Plantar Pressure for ACLD
  Patients
N2RPP: An Adversarial Network to Rebuild Plantar Pressure for ACLD Patients
Yi Zhang
Zhengfei Wang
Guoxiong Xu
Hongshi Huang
Wenxin Li
GANMedIm
14
0
0
08 May 2018
Unsupervised Learning using Pretrained CNN and Associative Memory Bank
Unsupervised Learning using Pretrained CNN and Associative Memory Bank
Qun Liu
S. Mukhopadhyay
60
37
0
02 May 2018
Internal node bagging
Internal node bagging
Shun Yi
BDL
29
0
0
01 May 2018
Universal approximations of invariant maps by neural networks
Universal approximations of invariant maps by neural networks
Dmitry Yarotsky
138
214
0
26 Apr 2018
STAN: Spatio-Temporal Adversarial Networks for Abnormal Event Detection
STAN: Spatio-Temporal Adversarial Networks for Abnormal Event Detection
Sangmin Lee
Hak Gu Kim
Yong Man Ro
3DPCGAN
60
83
0
23 Apr 2018
Understanding Regularization to Visualize Convolutional Neural Networks
Understanding Regularization to Visualize Convolutional Neural Networks
Maximilian Baust
Florian Ludwig
Christian Rupprecht
Matthias Kohl
S. Braunewell
FAtt
54
4
0
20 Apr 2018
Attacking Convolutional Neural Network using Differential Evolution
Attacking Convolutional Neural Network using Differential Evolution
Jiawei Su
Danilo Vasconcellos Vargas
Kouichi Sakurai
AAML
62
45
0
19 Apr 2018
IGCV$2$: Interleaved Structured Sparse Convolutional Neural Networks
IGCV222: Interleaved Structured Sparse Convolutional Neural Networks
Guotian Xie
Jingdong Wang
Ting Zhang
Jianhuang Lai
Richang Hong
Guo-Jun Qi
115
106
0
17 Apr 2018
Learning to Exploit the Prior Network Knowledge for Weakly-Supervised
  Semantic Segmentation
Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation
Carolina Redondo-Cabrera
Marcos Baptista-Rios
Roberto J. López-Sastre
60
34
0
13 Apr 2018
Pooling is neither necessary nor sufficient for appropriate deformation
  stability in CNNs
Pooling is neither necessary nor sufficient for appropriate deformation stability in CNNs
Avraham Ruderman
Neil C. Rabinowitz
Ari S. Morcos
Daniel Zoran
100
41
0
12 Apr 2018
VR IQA NET: Deep Virtual Reality Image Quality Assessment using
  Adversarial Learning
VR IQA NET: Deep Virtual Reality Image Quality Assessment using Adversarial Learning
Heoun-taek Lim
Hak Gu Kim
Yong Man Ro
33
48
0
11 Apr 2018
Ordinal Pooling Networks: For Preserving Information over Shrinking
  Feature Maps
Ordinal Pooling Networks: For Preserving Information over Shrinking Feature Maps
Ashwani Kumar
FAtt
38
8
0
08 Apr 2018
Towards radiologist-level cancer risk assessment in CT lung screening
  using deep learning
Towards radiologist-level cancer risk assessment in CT lung screening using deep learning
S. Trajanovski
Dimitrios Mavroeidis
C. Swisher
B. Gebre
Bastiaan S. Veeling
...
C. Wald
Brady J. McKee
Sebastian Flacke
H. MacMahon
H. Pien
49
51
0
05 Apr 2018
Convolutional Neural Networks Regularized by Correlated Noise
Convolutional Neural Networks Regularized by Correlated Noise
Shamak Dutta
B. Tripp
Graham W. Taylor
54
6
0
03 Apr 2018
DeepSigns: A Generic Watermarking Framework for IP Protection of Deep
  Learning Models
DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models
B. Rouhani
Huili Chen
F. Koushanfar
130
48
0
02 Apr 2018
The Resistance to Label Noise in K-NN and DNN Depends on its
  Concentration
The Resistance to Label Noise in K-NN and DNN Depends on its Concentration
Amnon Drory
Oria Ratzon
S. Avidan
Raja Giryes
41
16
0
30 Mar 2018
Parallel Grid Pooling for Data Augmentation
Parallel Grid Pooling for Data Augmentation
Akito Takeki
Daiki Ikami
Go Irie
Kiyoharu Aizawa
56
7
0
30 Mar 2018
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