CausAdv: A Causal-based Framework for Detecting Adversarial Examples
Authors: Hichem Debbi | Published: 2024-10-29
Adversarial Example
Integrating uncertainty quantification into randomized smoothing based robustness guarantees
Authors: Sina Däubener, Kira Maag, David Krueger, Asja Fischer | Published: 2024-10-27
Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
Authors: Binghui Li, Zhixuan Pan, Kaifeng Lyu, Jian Li | Published: 2024-10-14
Minimax rates of convergence for nonparametric regression under adversarial attacks
Authors: Jingfu Peng, Yuhong Yang | Published: 2024-10-12 | Updated: 2025-05-13
Time Traveling to Defend Against Adversarial Example Attacks in Image Classification
Authors: Anthony Etim, Jakub Szefer | Published: 2024-10-10
LOTOS: Layer-wise Orthogonalization for Training Robust Ensembles
Authors: Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran | Published: 2024-10-07
Impact of White-Box Adversarial Attacks on Convolutional Neural Networks
Authors: Rakesh Podder, Sudipto Ghosh | Published: 2024-10-02
On Using Certified Training towards Empirical Robustness
Authors: Alessandro De Palma, Serge Durand, Zakaria Chihani, François Terrier, Caterina Urban | Published: 2024-10-02 | Updated: 2025-03-24
Boosting Certified Robustness for Time Series Classification with Efficient Self-Ensemble
Authors: Chang Dong, Zhengyang Li, Liangwei Zheng, Weitong Chen, Wei Emma Zhang | Published: 2024-09-04 | Updated: 2024-09-19
Adversarial Attacks on Machine Learning-Aided Visualizations
Authors: Takanori Fujiwara, Kostiantyn Kucher, Junpeng Wang, Rafael M. Martins, Andreas Kerren, Anders Ynnerman | Published: 2024-09-04 | Updated: 2024-09-24