Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders

31 May 2018

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 321 10,591 0 17 Feb 2020
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 269 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 187 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 71 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 269 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 715 36,708 0 25 Aug 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 226 8,548 0 16 Aug 2016
Defensive Distillation is Not Robust to Adversarial Examples Nicholas Carlini D. Wagner 48 338 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 92 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 11 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 80 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 123 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 64 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 280 18,587 0 06 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.4K 149,842 0 22 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 233 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 239 14,893 1 21 Dec 2013