Explaining and Harnessing Adversarial Examples

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Explaining and Harnessing Adversarial Examples

20 December 2014

Jonathon Shlens

Christian Szegedy

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Papers citing "Explaining and Harnessing Adversarial Examples"

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Deep Learning and Music Adversaries Corey Kereliuk Bob L. T. Sturm J. Larsen AAML 85 137 0 16 Jul 2015
Semi-Supervised Learning with Ladder Networks Antti Rasmus Harri Valpola Mikko Honkala Mathias Berglund T. Raiko SSL 122 1,373 0 09 Jul 2015
Distributional Smoothing with Virtual Adversarial Training Takeru Miyato S. Maeda Masanori Koyama Ken Nakae S. Ishii 151 458 0 02 Jul 2015
Dropout as data augmentation Xavier Bouthillier K. Konda Pascal Vincent Roland Memisevic 151 134 0 29 Jun 2015
Understanding Neural Networks Through Deep Visualization J. Yosinski Jeff Clune Anh Totti Nguyen Thomas J. Fuchs Hod Lipson FAtt AI4CE 165 1,877 0 22 Jun 2015
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop Feng Yu Ari Seff Yinda Zhang Shuran Song Thomas Funkhouser Jianxiong Xiao 217 2,350 0 10 Jun 2015
Lateral Connections in Denoising Autoencoders Support Supervised Learning Antti Rasmus Harri Valpola T. Raiko 86 22 0 30 Apr 2015
Analysis of classifiers' robustness to adversarial perturbations Alhussein Fawzi Omar Fawzi P. Frossard AAML 115 360 0 09 Feb 2015
Qualitatively characterizing neural network optimization problems Ian Goodfellow Oriol Vinyals Andrew M. Saxe ODL 193 524 0 19 Dec 2014
Visual Causal Feature Learning Krzysztof Chalupka Pietro Perona F. Eberhardt CML OOD 105 141 0 07 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 221 3,280 0 05 Dec 2014
Qualitative Robustness in Bayesian Inference H. Owhadi C. Scovel 144 26 0 14 Nov 2014