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1806.00081
Cited By
Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders
31 May 2018
Partha Ghosh
Arpan Losalka
Michael J. Black
AAML
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Papers citing
"Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders"
32 / 32 papers shown
Title
Adversarial Examples on Object Recognition: A Comprehensive Survey
A. Serban
E. Poll
Joost Visser
AAML
78
73
0
07 Aug 2020
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
341
10,591
0
17 Feb 2020
Glow: Generative Flow with Invertible 1x1 Convolutions
Diederik P. Kingma
Prafulla Dhariwal
BDL
DRL
277
3,124
0
09 Jul 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models
Pouya Samangouei
Maya Kabkab
Rama Chellappa
AAML
GAN
82
1,176
0
17 May 2018
Adversarial Attacks Against Medical Deep Learning Systems
S. G. Finlayson
Hyung Won Chung
I. Kohane
Andrew L. Beam
SILM
AAML
OOD
MedIm
50
231
0
15 Apr 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
195
3,180
0
01 Feb 2018
Adversarial Examples: Attacks and Defenses for Deep Learning
Xiaoyong Yuan
Pan He
Qile Zhu
Xiaolin Li
SILM
AAML
86
1,618
0
19 Dec 2017
MagNet and "Efficient Defenses Against Adversarial Attacks" are Not Robust to Adversarial Examples
Nicholas Carlini
D. Wagner
AAML
53
248
0
22 Nov 2017
Generating Natural Adversarial Examples
Zhengli Zhao
Dheeru Dua
Sameer Singh
GAN
AAML
160
600
0
31 Oct 2017
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples
Yang Song
Taesup Kim
Sebastian Nowozin
Stefano Ermon
Nate Kushman
AAML
110
790
0
30 Oct 2017
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples
Pin-Yu Chen
Yash Sharma
Huan Zhang
Jinfeng Yi
Cho-Jui Hsieh
AAML
64
641
0
13 Sep 2017
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models
Pin-Yu Chen
Huan Zhang
Yash Sharma
Jinfeng Yi
Cho-Jui Hsieh
AAML
75
1,875
0
14 Aug 2017
Robust Physical-World Attacks on Deep Learning Models
Kevin Eykholt
Ivan Evtimov
Earlence Fernandes
Yue Liu
Amir Rahmati
Chaowei Xiao
Atul Prakash
Tadayoshi Kohno
D. Song
AAML
50
595
0
27 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
277
12,029
0
19 Jun 2017
MagNet: a Two-Pronged Defense against Adversarial Examples
Dongyu Meng
Hao Chen
AAML
46
1,206
0
25 May 2017
Delving into Transferable Adversarial Examples and Black-box Attacks
Yanpei Liu
Xinyun Chen
Chang-rui Liu
D. Song
AAML
133
1,731
0
08 Nov 2016
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
723
36,708
0
25 Aug 2016
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
237
8,548
0
16 Aug 2016
Defensive Distillation is Not Robust to Adversarial Examples
Nicholas Carlini
D. Wagner
56
338
0
14 Jul 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
SILM
AAML
100
1,738
0
24 May 2016
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
S. Jha
Z. Berkay Celik
A. Swami
MLAU
AAML
66
3,676
0
08 Feb 2016
Kernel principal component analysis network for image classification
Dan Wu
Jiasong Wu
Rui Zeng
Longyu Jiang
L. Senhadji
H. Shu
13
11
0
20 Dec 2015
The Limitations of Deep Learning in Adversarial Settings
Nicolas Papernot
Patrick McDaniel
S. Jha
Matt Fredrikson
Z. Berkay Celik
A. Swami
AAML
88
3,955
0
24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
131
4,886
0
14 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
Nicolas Papernot
Patrick McDaniel
Xi Wu
S. Jha
A. Swami
AAML
78
3,072
0
14 Nov 2015
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree
Chen-Yu Lee
Patrick W. Gallagher
Zhuowen Tu
AI4CE
73
484
0
30 Sep 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
288
18,587
0
06 Feb 2015
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.5K
149,842
0
22 Dec 2014
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
241
19,017
0
20 Dec 2014
Towards Deep Neural Network Architectures Robust to Adversarial Examples
S. Gu
Luca Rigazio
AAML
76
840
0
11 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
155
3,270
0
05 Dec 2014
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
247
14,893
1
21 Dec 2013
1