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Sensitivity Analysis of Deep Neural Networks

Sensitivity Analysis of Deep Neural Networks

22 January 2019
Hai Shu
Hongtu Zhu
    AAML
ArXiv (abs)PDFHTML

Papers citing "Sensitivity Analysis of Deep Neural Networks"

17 / 17 papers shown
Title
Sensitivity and Generalization in Neural Networks: an Empirical Study
Sensitivity and Generalization in Neural Networks: an Empirical Study
Roman Novak
Yasaman Bahri
Daniel A. Abolafia
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
AAML
99
442
0
23 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory
  Approach
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Tsui-Wei Weng
Huan Zhang
Pin-Yu Chen
Jinfeng Yi
D. Su
Yupeng Gao
Cho-Jui Hsieh
Luca Daniel
AAML
83
468
0
31 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A
  Survey
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Naveed Akhtar
Ajmal Mian
AAML
129
1,871
0
02 Jan 2018
One pixel attack for fooling deep neural networks
One pixel attack for fooling deep neural networks
Jiawei Su
Danilo Vasconcellos Vargas
Kouichi Sakurai
AAML
166
2,327
0
24 Oct 2017
Formal Guarantees on the Robustness of a Classifier against Adversarial
  Manipulation
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
Matthias Hein
Maksym Andriushchenko
AAML
129
512
0
23 May 2017
On the Robustness of Convolutional Neural Networks to Internal
  Architecture and Weight Perturbations
On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations
N. Cheney
Martin Schrimpf
Gabriel Kreiman
OOD
69
45
0
23 Mar 2017
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN3DV
892
36,910
0
25 Aug 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
284
8,593
0
16 Aug 2016
TensorFlow: A system for large-scale machine learning
TensorFlow: A system for large-scale machine learning
Martín Abadi
P. Barham
Jianmin Chen
Zhiwen Chen
Andy Davis
...
Vijay Vasudevan
Pete Warden
Martin Wicke
Yuan Yu
Xiaoqiang Zhang
GNNAI4CE
435
18,361
0
27 May 2016
End to End Learning for Self-Driving Cars
End to End Learning for Self-Driving Cars
Mariusz Bojarski
D. Testa
Daniel Dworakowski
Bernhard Firner
B. Flepp
...
Urs Muller
Jiakai Zhang
Xin Zhang
Jake Zhao
Karol Zieba
SSL
104
4,179
0
25 Apr 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.3K
194,641
0
10 Dec 2015
DeepFool: a simple and accurate method to fool deep neural networks
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
160
4,910
0
14 Nov 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
358
18,661
0
06 Feb 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
284
19,145
0
20 Dec 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLMObjD
1.7K
39,637
0
01 Sep 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
297
14,978
1
21 Dec 2013
Perturbation selection and influence measures in local influence
  analysis
Perturbation selection and influence measures in local influence analysis
Hong-Tu Zhu
J. Ibrahim
Sik-Yum Lee
Heping Zhang
323
117
0
20 Mar 2008
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