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
On the Importance of Gaussianizing Representations Daniel Eftekhari Vardan Papyan 26 0 0 01 May 2025
RESQUE: Quantifying Estimator to Task and Distribution Shift for Sustainable Model Reusability Vishwesh Sangarya Jung-Eun Kim 69 0 0 20 Dec 2024
Enhancing Adversarial Robustness via Uncertainty-Aware Distributional Adversarial Training Junhao Dong Xinghua Qu Zhiyuan Wang Yew-Soon Ong AAML 48 1 0 05 Nov 2024
Complexity Matters: Effective Dimensionality as a Measure for Adversarial Robustness David Khachaturov Robert D. Mullins AAML 25 0 0 24 Oct 2024
Stochastic Gradient Descent Jittering for Inverse Problems: Alleviating the Accuracy-Robustness Tradeoff Peimeng Guan Mark A. Davenport 28 0 0 18 Oct 2024
A practical approach to evaluating the adversarial distance for machine learning classifiers Georg Siedel Ekagra Gupta Andrey Morozov AAML 30 0 0 05 Sep 2024
Reassessing Noise Augmentation Methods in the Context of Adversarial Speech Karla Pizzi Matías Pizarro Asja Fischer 28 0 0 03 Sep 2024
First line of defense: A robust first layer mitigates adversarial attacks Janani Suresh Nancy Nayak Sheetal Kalyani AAML 22 0 0 21 Aug 2024
A-BDD: Leveraging Data Augmentations for Safe Autonomous Driving in Adverse Weather and Lighting Felix Assion Florens Gressner Nitin Augustine Jona Klemenc Ahmed Hammam Alexandre Krattinger Holger Trittenbach Sascha Riemer 31 1 0 12 Aug 2024
Label Augmentation for Neural Networks Robustness Fatemeh Amerehi Patrick Healy AAML 37 1 0 04 Aug 2024
Estimating Environmental Cost Throughout Model's Adaptive Life Cycle Vishwesh Sangarya Richard M. Bradford Jung-Eun Kim 19 2 0 23 Jul 2024
CTBENCH: A Library and Benchmark for Certified Training Yuhao Mao Stefan Balauca Martin Vechev OOD 47 4 0 07 Jun 2024
Inference Attacks: A Taxonomy, Survey, and Promising Directions Feng Wu Lei Cui Shaowen Yao Shui Yu 39 2 0 04 Jun 2024
Investigating and unmasking feature-level vulnerabilities of CNNs to adversarial perturbations Davide Coppola Hwee Kuan Lee AAML 47 0 0 31 May 2024
Aggregate Representation Measure for Predictive Model Reusability Vishwesh Sangarya Richard M. Bradford Jung-Eun Kim 27 2 0 15 May 2024
SeiT++: Masked Token Modeling Improves Storage-efficient Training Min-Seob Lee Song Park Byeongho Heo Dongyoon Han Hyunjung Shim MQ VLM 21 1 0 15 Dec 2023
Augment the Pairs: Semantics-Preserving Image-Caption Pair Augmentation for Grounding-Based Vision and Language Models Jingru Yi Burak Uzkent Oana Ignat Zili Li Amanmeet Garg Xiang Yu Linda Liu VLM 25 1 0 05 Nov 2023
Improving Robustness via Tilted Exponential Layer: A Communication-Theoretic Perspective Bhagyashree Puranik Ahmad Beirami Yao Qin Upamanyu Madhow AAML 15 0 0 02 Nov 2023
Dynamic Batch Norm Statistics Update for Natural Robustness Shahbaz Rezaei M. S. Norouzzadeh 8 0 0 31 Oct 2023
Data Optimization in Deep Learning: A Survey Ou Wu Rujing Yao 30 1 0 25 Oct 2023
Training Image Derivatives: Increased Accuracy and Universal Robustness V. Avrutskiy 36 0 0 21 Oct 2023
OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift Lin Li Yifei Wang Chawin Sitawarin Michael W. Spratling 24 0 0 19 Oct 2023
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control Neehal Tumma Mathias Lechner Noel Loo Ramin Hasani Daniela Rus 27 0 0 05 Oct 2023
Brain-like representational straightening of natural movies in robust feedforward neural networks Tahereh Toosi Elias B. Issa 20 5 0 26 Aug 2023
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds Hejia Geng Peng Li AAML 30 3 0 20 Aug 2023
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning Kaijie Zhu Jindong Wang Xixu Hu Xingxu Xie G. Yang AAML 22 23 0 01 Aug 2023
Learning Provably Robust Estimators for Inverse Problems via Jittering Anselm Krainovic Mahdi Soltanolkotabi Reinhard Heckel OOD 22 6 0 24 Jul 2023
A Theoretical Perspective on Subnetwork Contributions to Adversarial Robustness Jovon Craig Joshua Andle Theodore S. Nowak S. Y. Sekeh AAML 34 0 0 07 Jul 2023
Generalization Across Experimental Parameters in Machine Learning Analysis of High Resolution Transmission Electron Microscopy Datasets Katherine Sytwu L. Dacosta M. Scott 11 2 0 20 Jun 2023
Exploiting Frequency Spectrum of Adversarial Images for General Robustness Chun Yang Tan K. Kawamoto Hiroshi Kera AAML OOD 26 1 0 15 May 2023
Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm Corruptions George J. Siedel Weijia Shao S. Vock Andrey Morozov 17 1 0 09 May 2023
Hint-Aug: Drawing Hints from Foundation Vision Transformers Towards Boosted Few-Shot Parameter-Efficient Tuning Zhongzhi Yu Shang Wu Y. Fu Shunyao Zhang Yingyan Lin 25 6 0 25 Apr 2023
AI Security Threats against Pervasive Robotic Systems: A Course for Next Generation Cybersecurity Workforce Sudip Mittal Jingdao Chen SILM 23 1 0 15 Feb 2023
Semantic Image Segmentation: Two Decades of Research G. Csurka Riccardo Volpi Boris Chidlovskii 3DV 24 50 0 13 Feb 2023
Linking convolutional kernel size to generalization bias in face analysis CNNs Hao Liang J. O. Caro Vikram Maheshri Ankit B. Patel Guha Balakrishnan CVBM CML 13 0 0 07 Feb 2023
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection A. Ćiprijanović Ashia Lewis K. Pedro Sandeep Madireddy Brian D. Nord G. Perdue Stefan M. Wild 36 14 0 03 Feb 2023
A Theoretical Study of The Effects of Adversarial Attacks on Sparse Regression Deepak Maurya Jean Honorio AAML 14 0 0 21 Dec 2022
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization Shiji Xin Yifei Wang Jingtong Su Yisen Wang OOD 21 7 0 18 Dec 2022
What does a deep neural network confidently perceive? The effective dimension of high certainty class manifolds and their low confidence boundaries Stanislav Fort E. D. Cubuk Surya Ganguli S. Schoenholz 12 5 0 11 Oct 2022
Learning Robust Kernel Ensembles with Kernel Average Pooling P. Bashivan Adam Ibrahim Amirozhan Dehghani Yifei Ren OOD 16 5 0 30 Sep 2022
Measuring Overfitting in Convolutional Neural Networks using Adversarial Perturbations and Label Noise Svetlana Pavlitskaya Joël Oswald J. Marius Zöllner NoLa AAML 22 5 0 27 Sep 2022
Revisiting Outer Optimization in Adversarial Training Ali Dabouei Fariborz Taherkhani Sobhan Soleymani Nasser M. Nasrabadi AAML 19 4 0 02 Sep 2022
Robust Prototypical Few-Shot Organ Segmentation with Regularized Neural-ODEs Prashant Pandey Mustafa Chasmai Tanuj Sur Brejesh Lall 8 11 0 26 Aug 2022
A Novel Plug-and-Play Approach for Adversarially Robust Generalization Deepak Maurya Adarsh Barik Jean Honorio OOD AAML 27 0 0 19 Aug 2022
Abutting Grating Illusion: Cognitive Challenge to Neural Network Models Jinyu Fan Yi Zeng AAML 29 1 0 08 Aug 2022
$p$ -DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations Adam Dziedzic Stephan Rabanser Mohammad Yaghini Armin Ale Murat A. Erdogdu Nicolas Papernot AAML 15 2 0 25 Jul 2022
Bounding generalization error with input compression: An empirical study with infinite-width networks A. Galloway A. Golubeva Mahmoud Salem Mihai Nica Yani Andrew Ioannou Graham W. Taylor MLT AI4CE 24 4 0 19 Jul 2022
Utilizing Class Separation Distance for the Evaluation of Corruption Robustness of Machine Learning Classifiers George J. Siedel S. Vock Andrey Morozov Stefan Voss 6 3 0 27 Jun 2022
Measuring Lower Bounds of Local Differential Privacy via Adversary Instantiations in Federated Learning Marin Matsumoto Tsubasa Takahashi Seng Pei Liew M. Oguchi FedML BDL 15 0 0 18 Jun 2022
Noisy Learning for Neural ODEs Acts as a Robustness Locus Widening Martin Gonzalez H. Hajri Loic Cantat M. Petreczky 27 1 0 16 Jun 2022