Excessive Invariance Causes Adversarial Vulnerability

1 November 2018

Papers citing "Excessive Invariance Causes Adversarial Vulnerability"

47 / 47 papers shown

Title
FedAT: Federated Adversarial Training for Distributed Insider Threat Detection R. Gayathri Atul Sajjanhar Md Palash Uddin Yong Xiang FedML 23 0 0 19 Sep 2024
Input Space Mode Connectivity in Deep Neural Networks Jakub Vrabel Ori Shem-Ur Yaron Oz David Krueger 56 1 0 09 Sep 2024
Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations Justin Deschenaux Igor Krawczuk Grigorios G. Chrysos V. Cevher DiffM 52 3 0 29 May 2024
Training Image Derivatives: Increased Accuracy and Universal Robustness V. Avrutskiy 46 0 0 21 Oct 2023
Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck Jongheon Jeong Sihyun Yu Hankook Lee Jinwoo Shin AAML 44 0 0 24 Mar 2023
Training Invertible Neural Networks as Autoencoders The-Gia Leo Nguyen Lynton Ardizzone Ullrich Kothe BDL DRL SSL 30 9 0 20 Mar 2023
It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness Peiyu Xiong Michael W. Tegegn Jaskeerat Singh Sarin Shubhraneel Pal Julia Rubin SILM AAML 32 8 0 17 Mar 2023
Transformed Distribution Matching for Missing Value Imputation He Zhao Ke Sun Amir Dezfouli Edwin V. Bonilla 34 19 0 20 Feb 2023
Certified Invertibility in Neural Networks via Mixed-Integer Programming Tianqi Cui Tom S. Bertalan George J. Pappas M. Morari Ioannis G. Kevrekidis Mahyar Fazlyab AAML 27 2 0 27 Jan 2023
Differentiable Dictionary Search: Integrating Linear Mixing with Deep Non-Linear Modelling for Audio Source Separation Lukávs Samuel Marták Rainer Kelz Gerhard Widmer 23 1 0 28 Nov 2022
Mechanistic Mode Connectivity Ekdeep Singh Lubana Eric J. Bigelow Robert P. Dick David M. Krueger Hidenori Tanaka 32 45 0 15 Nov 2022
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? Henry Kvinge Tegan H. Emerson Grayson Jorgenson Scott Vasquez T. Doster Jesse D. Lew 51 8 0 07 Oct 2022
Bispectral Neural Networks Sophia Sanborn Christian Shewmake Bruno A. Olshausen Christopher Hillar 37 12 0 07 Sep 2022
Distributional Gaussian Processes Layers for Out-of-Distribution Detection S. Popescu D. Sharp James H. Cole Konstantinos Kamnitsas Ben Glocker OOD 29 0 0 27 Jun 2022
On the Limitations of Stochastic Pre-processing Defenses Yue Gao Ilia Shumailov Kassem Fawaz Nicolas Papernot AAML SILM 47 30 0 19 Jun 2022
Exact Feature Collisions in Neural Networks Utku Ozbulak Manvel Gasparyan Shodhan Rao W. D. Neve Arnout Van Messem AAML 27 1 0 31 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 26 48 0 01 May 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations Polina Kirichenko Pavel Izmailov A. Wilson OOD 49 318 0 06 Apr 2022
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 49 72 0 26 Mar 2022
Fourier-Based Augmentations for Improved Robustness and Uncertainty Calibration Ryan Soklaski Michael Yee Theodoros Tsiligkaridis AAML 19 14 0 24 Feb 2022
Disentanglement and Generalization Under Correlation Shifts Christina M. Funke Paul Vicol Kuan-Chieh Jackson Wang Matthias Kümmerer R. Zemel Matthias Bethge OOD 39 7 0 29 Dec 2021
Understanding Square Loss in Training Overparametrized Neural Network Classifiers Tianyang Hu Jun Wang Wei Cao Zhenguo Li UQCV AAML 41 19 0 07 Dec 2021
Decomposing Representations for Deterministic Uncertainty Estimation Haiwen Huang Joost R. van Amersfoort Y. Gal UQCV OOD UD 32 1 0 01 Dec 2021
Calibrated Adversarial Training Tianjin Huang Vlado Menkovski Yulong Pei Mykola Pechenizkiy AAML 56 3 0 01 Oct 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 31 236 0 01 Aug 2021
Can contrastive learning avoid shortcut solutions? Joshua Robinson Li Sun Ke Yu Kayhan Batmanghelich Stefanie Jegelka S. Sra SSL 19 142 0 21 Jun 2021
Conditional Invertible Neural Networks for Diverse Image-to-Image Translation Lynton Ardizzone Jakob Kruse Carsten T. Lüth Niels Bracher Carsten Rother Ullrich Kothe 21 31 0 05 May 2021
DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning Olakunle Ibitoye M. O. Shafiq Ashraf Matrawy FedML 28 18 0 08 Jan 2021
A case for new neural network smoothness constraints Mihaela Rosca T. Weber Arthur Gretton S. Mohamed AAML 35 48 0 14 Dec 2020
Gradient Starvation: A Learning Proclivity in Neural Networks Mohammad Pezeshki Sekouba Kaba Yoshua Bengio Aaron Courville Doina Precup Guillaume Lajoie MLT 50 257 0 18 Nov 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 29 48 0 19 Oct 2020
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective Wei Ping Shuohang Wang Yu Cheng Zhe Gan R. Jia Bo-wen Li Jingjing Liu AAML 46 113 0 05 Oct 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor A. Madry 37 417 0 16 Jul 2020
Seeing eye-to-eye? A comparison of object recognition performance in humans and deep convolutional neural networks under image manipulation Leonard E. van Dyck W. Gruber 27 3 0 13 Jul 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip Torr NoLa AAML 23 57 0 08 Jul 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 37 437 0 17 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Jackson Wang Roger C. Grosse J. Jacobsen 23 93 0 16 Jun 2020
Going in circles is the way forward: the role of recurrence in visual inference R. S. V. Bergen N. Kriegeskorte 17 82 0 26 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 Mar 2020
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 23 230 0 24 Jul 2019
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation Raphael Gontijo-Lopes Dong Yin Ben Poole Justin Gilmer E. D. Cubuk AAML 33 204 0 06 Jun 2019
Adversarial Robustness as a Prior for Learned Representations Logan Engstrom Andrew Ilyas Shibani Santurkar Dimitris Tsipras Brandon Tran A. Madry OOD AAML 27 63 0 03 Jun 2019
DIVA: Domain Invariant Variational Autoencoders Maximilian Ilse Jakub M. Tomczak Christos Louizos Max Welling DRL OOD 28 198 0 24 May 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 22 46 0 25 Mar 2019
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 25 618 0 02 Nov 2018
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 65 230 0 25 May 2018
Constructing Unrestricted Adversarial Examples with Generative Models Yang Song Rui Shu Nate Kushman Stefano Ermon GAN AAML 185 302 0 21 May 2018