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Wide Residual Networks
v1v2v3v4 (latest)

Wide Residual Networks

23 May 2016
Sergey Zagoruyko
N. Komodakis
ArXiv (abs)PDFHTMLGithub (1306★)

Papers citing "Wide Residual Networks"

50 / 4,147 papers shown
Title
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks
Denny Zhou
Mao Ye
Chen Chen
Tianjian Meng
Mingxing Tan
Xiaodan Song
Quoc V. Le
Qiang Liu
Dale Schuurmans
63
20
0
01 Jul 2020
Adversarial Example Games
Adversarial Example Games
A. Bose
Gauthier Gidel
Hugo Berrard
Andre Cianflone
Pascal Vincent
Simon Lacoste-Julien
William L. Hamilton
AAMLGAN
115
52
0
01 Jul 2020
ConFoc: Content-Focus Protection Against Trojan Attacks on Neural
  Networks
ConFoc: Content-Focus Protection Against Trojan Attacks on Neural Networks
Miguel Villarreal-Vasquez
B. Bhargava
AAML
98
39
0
01 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image
  Classification
Measuring Robustness to Natural Distribution Shifts in Image Classification
Rohan Taori
Achal Dave
Vaishaal Shankar
Nicholas Carlini
Benjamin Recht
Ludwig Schmidt
OOD
132
549
0
01 Jul 2020
Temporal Calibrated Regularization for Robust Noisy Label Learning
Temporal Calibrated Regularization for Robust Noisy Label Learning
Dongxian Wu
Yisen Wang
Zhuobin Zheng
Shutao Xia
NoLa
43
2
0
01 Jul 2020
Improving robustness against common corruptions by covariate shift
  adaptation
Improving robustness against common corruptions by covariate shift adaptation
Steffen Schneider
E. Rusak
L. Eck
Oliver Bringmann
Wieland Brendel
Matthias Bethge
VLM
101
486
0
30 Jun 2020
Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey
Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey
M. Rath
Alexandru Paul Condurache
ViTAI4CE
114
9
0
30 Jun 2020
Guided Learning of Nonconvex Models through Successive Functional
  Gradient Optimization
Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization
Rie Johnson
Tong Zhang
23
8
0
30 Jun 2020
Classification Confidence Estimation with Test-Time Data-Augmentation
Classification Confidence Estimation with Test-Time Data-Augmentation
Yuval Bahat
Gregory Shakhnarovich
57
18
0
30 Jun 2020
On the Demystification of Knowledge Distillation: A Residual Network
  Perspective
On the Demystification of Knowledge Distillation: A Residual Network Perspective
N. Jha
Rajat Saini
Sparsh Mittal
47
4
0
30 Jun 2020
Actionable Attribution Maps for Scientific Machine Learning
Actionable Attribution Maps for Scientific Machine Learning
Shusen Liu
B. Kailkhura
Jize Zhang
A. Hiszpanski
Emily Robertson
Donald Loveland
T. Y. Han
21
1
0
30 Jun 2020
Uniform Priors for Data-Efficient Transfer
Uniform Priors for Data-Efficient Transfer
Samarth Sinha
Karsten Roth
Anirudh Goyal
Marzyeh Ghassemi
Hugo Larochelle
Animesh Garg
OOD
121
0
0
30 Jun 2020
Improving Calibration through the Relationship with Adversarial
  Robustness
Improving Calibration through the Relationship with Adversarial Robustness
Yao Qin
Xuezhi Wang
Alex Beutel
Ed H. Chi
AAML
86
25
0
29 Jun 2020
Asymmetric metric learning for knowledge transfer
Asymmetric metric learning for knowledge transfer
Mateusz Budnik
Yannis Avrithis
69
35
0
29 Jun 2020
Improving Few-Shot Learning using Composite Rotation based Auxiliary
  Task
Improving Few-Shot Learning using Composite Rotation based Auxiliary Task
Pratik Mazumder
Pravendra Singh
Vinay P. Namboodiri
72
9
0
29 Jun 2020
Laplacian Regularized Few-Shot Learning
Laplacian Regularized Few-Shot Learning
Imtiaz Masud Ziko
Jose Dolz
Eric Granger
Ismail Ben Ayed
82
176
0
28 Jun 2020
Listen carefully and tell: an audio captioning system based on residual
  learning and gammatone audio representation
Listen carefully and tell: an audio captioning system based on residual learning and gammatone audio representation
Sergi Perez-Castanos
Javier Naranjo-Alcazar
P. Zuccarello
M. Cobos
70
11
0
27 Jun 2020
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
Jiefeng Chen
Yixuan Li
Xi Wu
Yingyu Liang
S. Jha
OODD
102
140
0
26 Jun 2020
On the Generalization Benefit of Noise in Stochastic Gradient Descent
On the Generalization Benefit of Noise in Stochastic Gradient Descent
Samuel L. Smith
Erich Elsen
Soham De
MLT
62
100
0
26 Jun 2020
Ensemble Transfer Learning for Emergency Landing Field Identification on
  Moderate Resource Heterogeneous Kubernetes Cluster
Ensemble Transfer Learning for Emergency Landing Field Identification on Moderate Resource Heterogeneous Kubernetes Cluster
Andreas Klos
Marius Rosenbaum
W. Schiffmann
26
3
0
26 Jun 2020
Proper Network Interpretability Helps Adversarial Robustness in
  Classification
Proper Network Interpretability Helps Adversarial Robustness in Classification
Akhilan Boopathy
Sijia Liu
Gaoyuan Zhang
Cynthia Liu
Pin-Yu Chen
Shiyu Chang
Luca Daniel
AAMLFAtt
123
66
0
26 Jun 2020
Learning Data Augmentation with Online Bilevel Optimization for Image
  Classification
Learning Data Augmentation with Online Bilevel Optimization for Image Classification
Saypraseuth Mounsaveng
I. Laradji
Ismail Ben Ayed
David Vazquez
M. Pedersoli
67
36
0
25 Jun 2020
Fully Convolutional Open Set Segmentation
Fully Convolutional Open Set Segmentation
Hugo Oliveira
C. Silva
Gabriel L. S. Machado
Keiller Nogueira
J. A. dos Santos
SSeg
96
28
0
25 Jun 2020
Epoch-evolving Gaussian Process Guided Learning
Epoch-evolving Gaussian Process Guided Learning
Jiabao Cui
Xuewei Li
Bin Li
Hanbin Zhao
Bourahla Omar
Xi Li
BDL
41
0
0
25 Jun 2020
Time for a Background Check! Uncovering the impact of Background
  Features on Deep Neural Networks
Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks
Vikash Sehwag
Rajvardhan Oak
M. Chiang
Prateek Mittal
FAtt
64
7
0
24 Jun 2020
Feature-Dependent Cross-Connections in Multi-Path Neural Networks
Feature-Dependent Cross-Connections in Multi-Path Neural Networks
Dumindu Tissera
H. W. M. K. Vithanage
Rukshan Wijesinghe
Kumara Kahatapitiya
Subha Fernando
Ranga Rodrigo
30
3
0
24 Jun 2020
Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial
  Robustness
Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness
Xingjun Ma
Linxi Jiang
Hanxun Huang
Zejia Weng
James Bailey
Yu-Gang Jiang
AAML
77
10
0
24 Jun 2020
On the Empirical Neural Tangent Kernel of Standard Finite-Width
  Convolutional Neural Network Architectures
On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures
M. Samarin
Volker Roth
David Belius
48
3
0
24 Jun 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification
Hyperparameter Ensembles for Robustness and Uncertainty Quantification
F. Wenzel
Jasper Snoek
Dustin Tran
Rodolphe Jenatton
UQCV
112
212
0
24 Jun 2020
Ramanujan Bipartite Graph Products for Efficient Block Sparse Neural
  Networks
Ramanujan Bipartite Graph Products for Efficient Block Sparse Neural Networks
Dharma Teja Vooturi
G. Varma
Kishore Kothapalli
47
6
0
24 Jun 2020
Multi-Class Uncertainty Calibration via Mutual Information
  Maximization-based Binning
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning
Kanil Patel
William H. Beluch
Binh Yang
Michael Pfeiffer
Dan Zhang
UQCV
113
34
0
23 Jun 2020
Post-hoc Calibration of Neural Networks by g-Layers
Post-hoc Calibration of Neural Networks by g-Layers
Amir M. Rahimi
Thomas Mensink
Kartik Gupta
Thalaiyasingam Ajanthan
C. Sminchisescu
Leonid Sigal
64
6
0
23 Jun 2020
Calibration of Neural Networks using Splines
Calibration of Neural Networks using Splines
Kartik Gupta
Amir M. Rahimi
Thalaiyasingam Ajanthan
Thomas Mensink
C. Sminchisescu
Leonid Sigal
97
109
0
23 Jun 2020
RayS: A Ray Searching Method for Hard-label Adversarial Attack
RayS: A Ray Searching Method for Hard-label Adversarial Attack
Jinghui Chen
Quanquan Gu
AAML
85
139
0
23 Jun 2020
The Depth-to-Width Interplay in Self-Attention
The Depth-to-Width Interplay in Self-Attention
Yoav Levine
Noam Wies
Or Sharir
Hofit Bata
Amnon Shashua
137
46
0
22 Jun 2020
Effective Version Space Reduction for Convolutional Neural Networks
Effective Version Space Reduction for Convolutional Neural Networks
Jiayu Liu
Ioannis Chiotellis
Rudolph Triebel
Zorah Lähner
19
2
0
22 Jun 2020
Learning to Generate Noise for Multi-Attack Robustness
Learning to Generate Noise for Multi-Attack Robustness
Divyam Madaan
Jinwoo Shin
Sung Ju Hwang
NoLaAAML
145
25
0
22 Jun 2020
Towards Understanding Label Smoothing
Towards Understanding Label Smoothing
Yi Tian Xu
Yuanhong Xu
Qi Qian
Hao Li
Rong Jin
UQCV
55
42
0
20 Jun 2020
Deep Polynomial Neural Networks
Deep Polynomial Neural Networks
Grigorios G. Chrysos
Stylianos Moschoglou
Giorgos Bouritsas
Jiankang Deng
Yannis Panagakis
Stefanos Zafeiriou
89
94
0
20 Jun 2020
Paying more attention to snapshots of Iterative Pruning: Improving Model
  Compression via Ensemble Distillation
Paying more attention to snapshots of Iterative Pruning: Improving Model Compression via Ensemble Distillation
Duong H. Le
Vo Trung Nhan
N. Thoai
VLM
54
7
0
20 Jun 2020
Denoising Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
DiffM
1.0K
18,531
0
19 Jun 2020
Towards an Adversarially Robust Normalization Approach
Towards an Adversarially Robust Normalization Approach
Muhammad Awais
Fahad Shamshad
Sung-Ho Bae
AAMLOOD
114
19
0
19 Jun 2020
Cyclic Differentiable Architecture Search
Cyclic Differentiable Architecture Search
Hongyuan Yu
Houwen Peng
Yan Huang
Jianlong Fu
Hao Du
Liang Wang
Haibin Ling
3DPC
123
48
0
18 Jun 2020
Neural Parameter Allocation Search
Neural Parameter Allocation Search
Bryan A. Plummer
Nikoli Dryden
Julius Frost
Torsten Hoefler
Kate Saenko
120
16
0
18 Jun 2020
What Do Neural Networks Learn When Trained With Random Labels?
What Do Neural Networks Learn When Trained With Random Labels?
Hartmut Maennel
Ibrahim Alabdulmohsin
Ilya O. Tolstikhin
R. Baldock
Olivier Bousquet
Sylvain Gelly
Daniel Keysers
FedML
167
90
0
18 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep
  Learning via Distance Awareness
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Jeremiah Zhe Liu
Zi Lin
Shreyas Padhy
Dustin Tran
Tania Bedrax-Weiss
Balaji Lakshminarayanan
UQCVBDL
290
453
0
17 Jun 2020
Noise or Signal: The Role of Image Backgrounds in Object Recognition
Noise or Signal: The Role of Image Backgrounds in Object Recognition
Kai Y. Xiao
Logan Engstrom
Andrew Ilyas
Aleksander Madry
175
388
0
17 Jun 2020
Optimizing Grouped Convolutions on Edge Devices
Optimizing Grouped Convolutions on Edge Devices
Perry Gibson
José Cano
Jack Turner
Elliot J. Crowley
Michael F. P. O'Boyle
Amos Storkey
55
25
0
17 Jun 2020
Mitosis Detection Under Limited Annotation: A Joint Learning Approach
Mitosis Detection Under Limited Annotation: A Joint Learning Approach
Pushpak Pati
A. Foncubierta-Rodríguez
Orçun Göksel
M. Gabrani
29
6
0
17 Jun 2020
Building One-Shot Semi-supervised (BOSS) Learning up to Fully Supervised
  Performance
Building One-Shot Semi-supervised (BOSS) Learning up to Fully Supervised Performance
L. Smith
A. Conovaloff
SSL
75
8
0
16 Jun 2020
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