adversarial perturbation

Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing NeurIPS 2020 Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks ICLR 2020 ML-LOO: Detecting Adversarial Examples with Feature Attribution AAAI 2020 Most ReLU Networks Suffer from ℓ^2 Adversarial Perturbations NeurIPS 2020 Neural Network Control Policy Verification With Persistent Adversarial Perturbation ICML 2020 Non-Stochastic Control with Bandit Feedback NeurIPS 2020 On the Robustness of Data-Driven Controllers for Linear Systems L4DC 2020 Probabilistic Safety for Bayesian Neural Networks UAI 2020 Provable robustness against all adversarial l_p-perturbations for p≥ 1 ICLR 2020 Provably Robust Metric Learning NeurIPS 2020 Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation AAAI 2020 Robust Superpixel-Guided Attentional Adversarial Attack CVPR 2020 SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations WACV 2020 Speaker Identification for Household Scenarios with Self-Attention and Adversarial Training Interspeech 2020 Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning AAAI 2020 Targeted Adversarial Perturbations for Monocular Depth Prediction NeurIPS 2020 The Nonstochastic Control Problem ALT 2020 The Pitfalls of Simplicity Bias in Neural Networks NeurIPS 2020 Towards Large Yet Imperceptible Adversarial Image Perturbations With Perceptual Color Distance CVPR 2020 Unrestricted Adversarial Examples via Semantic Manipulation ICLR 2020 Accurate, reliable and fast robustness evaluation NeurIPS 2019 Adversarial Attacks on Neural Networks for Graph Data IJCAI 2019 Adversarial Defense by Stratified Convolutional Sparse Coding CVPR 2019 Adversarial Examples for Graph Data: Deep Insights into Attack and Defense IJCAI 2019 Adversarial Reprogramming of Neural Networks ICLR 2019