Adversarial Examples Are a Natural Consequence of Test Error in Noise

29 January 2019

Justin Gilmer

Papers citing "Adversarial Examples Are a Natural Consequence of Test Error in Noise"

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Title
Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks Daniel Schwalbe-Koda Aik Rui Tan Rafael Gómez-Bombarelli AAML 21 60 0 27 Jan 2021
Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds B. Georgiev L. Franken Mayukh Mukherjee AAML 13 1 0 15 Jan 2021
Robusta: Robust AutoML for Feature Selection via Reinforcement Learning Xiaoyang Sean Wang Bo-wen Li Yibo Zhang B. Kailkhura K. Nahrstedt 8 3 0 15 Jan 2021
Learning Robust Representation for Clustering through Locality Preserving Variational Discriminative Network Ruixuan Luo Wei Li Zhiyuan Zhang Ruihan Bao Keiko Harimoto Xu Sun OOD DRL 23 1 0 25 Dec 2020
Adversarial Momentum-Contrastive Pre-Training Cong Xu Dan Li Min Yang SSL 19 15 0 24 Dec 2020
Dataset of Random Relaxations for Crystal Structure Search of Li-Si System Gowoon Cheon Lusann Yang Kevin McCloskey E. Reed E. D. Cubuk 8 0 0 05 Dec 2020
Contextual Fusion For Adversarial Robustness Aiswarya Akumalla S. Haney M. Bazhenov AAML 22 1 0 18 Nov 2020
Golden Grain: Building a Secure and Decentralized Model Marketplace for MLaaS Jiasi Weng Jian Weng Chengjun Cai Hongwei Huang Cong Wang AI4TS 11 20 0 12 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 41 8 0 03 Nov 2020
Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise Accuracy Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 11 56 0 26 Oct 2020
ATRO: Adversarial Training with a Rejection Option Masahiro Kato Zhenghang Cui Yoshihiro Fukuhara AAML 18 11 0 24 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 219 676 0 19 Oct 2020
Verifying the Causes of Adversarial Examples Honglin Li Yifei Fan F. Ganz A. Yezzi Payam Barnaghi AAML 10 3 0 19 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 21 48 0 19 Oct 2020
Linking average- and worst-case perturbation robustness via class selectivity and dimensionality Matthew L. Leavitt Ari S. Morcos AAML 6 2 0 14 Oct 2020
Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers Christoph Kamann Burkhard Güssefeld Robin Hutmacher J. H. Metzen Carsten Rother 6 18 0 12 Oct 2020
Revisiting Batch Normalization for Improving Corruption Robustness Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon 6 82 0 07 Oct 2020
Batch Normalization Increases Adversarial Vulnerability and Decreases Adversarial Transferability: A Non-Robust Feature Perspective Philipp Benz Chaoning Zhang In So Kweon AAML 4 39 0 07 Oct 2020
Adversarial and Natural Perturbations for General Robustness Sadaf Gulshad J. H. Metzen A. Smeulders AAML OOD 8 3 0 03 Oct 2020
Adversarial robustness via stochastic regularization of neural activation sensitivity Gil Fidel Ron Bitton Ziv Katzir A. Shabtai AAML 11 1 0 23 Sep 2020
BREEDS: Benchmarks for Subpopulation Shift Shibani Santurkar Dimitris Tsipras A. Madry OOD 8 168 0 11 Aug 2020
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective Baifeng Shi Dinghuai Zhang Qi Dai Zhanxing Zhu Yadong Mu Jingdong Wang OOD 14 111 0 10 Aug 2020
Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations Ziquan Liu Yufei Cui Antoni B. Chan 12 13 0 07 Aug 2020
Label-Only Membership Inference Attacks Christopher A. Choquette-Choo Florian Tramèr Nicholas Carlini Nicolas Papernot MIACV MIALM 13 493 0 28 Jul 2020
Adversarial Attacks against Face Recognition: A Comprehensive Study Fatemeh Vakhshiteh A. Nickabadi Raghavendra Ramachandra AAML 13 16 0 22 Jul 2020
Robust Image Classification Using A Low-Pass Activation Function and DCT Augmentation Md Tahmid Hossain S. Teng Ferdous Sohel Guojun Lu 8 10 0 18 Jul 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 22 956 0 16 Jul 2020
Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations Chaoning Zhang Philipp Benz Tooba Imtiaz In-So Kweon SSL AAML 6 117 0 13 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification Rohan Taori Achal Dave Vaishaal Shankar Nicholas Carlini Benjamin Recht Ludwig Schmidt OOD 22 530 0 01 Jul 2020
Improving robustness against common corruptions by covariate shift adaptation Steffen Schneider E. Rusak L. Eck Oliver Bringmann Wieland Brendel Matthias Bethge VLM 31 457 0 30 Jun 2020
Conditional GAN for timeseries generation Kaleb E. Smith Anthony O. Smith AI4TS 6 77 0 30 Jun 2020
Local Convolutions Cause an Implicit Bias towards High Frequency Adversarial Examples J. O. Caro Yilong Ju Ryan Pyle Sourav Dey Wieland Brendel Fabio Anselmi Ankit B. Patel AAML 6 10 0 19 Jun 2020
A general framework for defining and optimizing robustness Alessandro Tibo M. Jaeger Kim G. Larsen 10 0 0 19 Jun 2020
Towards an Adversarially Robust Normalization Approach Muhammad Awais Fahad Shamshad Sung-Ho Bae AAML OOD 33 19 0 19 Jun 2020
Classifier-independent Lower-Bounds for Adversarial Robustness Elvis Dohmatob 9 1 0 17 Jun 2020
The shape and simplicity biases of adversarially robust ImageNet-trained CNNs Peijie Chen Chirag Agarwal Anh Totti Nguyen AAML 6 16 0 16 Jun 2020
Consistency Regularization for Certified Robustness of Smoothed Classifiers Jongheon Jeong Jinwoo Shin AAML 12 88 0 07 Jun 2020
Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity Nam Ho-Nguyen Stephen J. Wright OOD 32 16 0 28 May 2020
Investigating Vulnerability to Adversarial Examples on Multimodal Data Fusion in Deep Learning Youngjoon Yu Hong Joo Lee Byeong Cheon Kim Jung Uk Kim Yong Man Ro AAML 30 18 0 22 May 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 27 146 0 20 May 2020
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural Networks Linhai Ma Liang Liang AAML 18 18 0 19 May 2020
Adversarial Robustness Guarantees for Random Deep Neural Networks Giacomo De Palma B. Kiani S. Lloyd AAML OOD 11 8 0 13 Apr 2020
Luring of transferable adversarial perturbations in the black-box paradigm Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML 15 2 0 10 Apr 2020
SOAR: Second-Order Adversarial Regularization A. Ma Fartash Faghri Nicolas Papernot Amir-massoud Farahmand AAML 10 4 0 04 Apr 2020
Towards Deep Learning Models Resistant to Large Perturbations Amirreza Shaeiri Rozhin Nobahari M. Rohban OOD AAML 18 12 0 30 Mar 2020
Heat and Blur: An Effective and Fast Defense Against Adversarial Examples Haya Brama Tal Grinshpoun AAML 6 6 0 17 Mar 2020
Metrics and methods for robustness evaluation of neural networks with generative models Igor Buzhinsky Arseny Nerinovsky S. Tripakis AAML 28 25 0 04 Mar 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 9 6 0 28 Feb 2020
Gödel's Sentence Is An Adversarial Example But Unsolvable Xiaodong Qi Lansheng Han AAML 12 0 0 25 Feb 2020
Boosting Adversarial Training with Hypersphere Embedding Tianyu Pang Xiao Yang Yinpeng Dong Kun Xu Jun Zhu Hang Su AAML 16 154 0 20 Feb 2020