adversarial robustness

Not All Low-Pass Filters are Robust in Graph Convolutional Networks NeurIPS 2021 On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning ICLR 2021 On Linear Stability of SGD and Input-Smoothness of Neural Networks NeurIPS 2021 On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory AAAI 2021 On Locality of Local Explanation Models NeurIPS 2021 On Robustness of Neural Semantic Parsers EACL 2021 On Smoother Attributions using Neural Stochastic Differential Equations IJCAI 2021 On the Existence of The Adversarial Bayes Classifier NeurIPS 2021 On the Generalization Properties of Adversarial Training AISTATS 2021 On the Robustness of Vision Transformers to Adversarial Examples ICCV 2021 On the Transferability of Minimal Prediction Preserving Inputs in Question Answering NAACL 2021 OpenAttack: An Open-source Textual Adversarial Attack Toolkit ACL 2021 Optimal query complexity for private sequential learning against eavesdropping AISTATS 2021 Orthogonalizing Convolutional Layers with the Cayley Transform ICLR 2021 Overcoming the Convex Barrier for Simplex Inputs NeurIPS 2021 Perceptual Adversarial Robustness: Defense Against Unseen Threat Models ICLR 2021 PointGuard: Provably Robust 3D Point Cloud Classification CVPR 2021 Posterior Differential Regularization with f-divergence for Improving Model Robustness NAACL 2021 Power up! Robust Graph Convolutional Network via Graph Powering AAAI 2021 Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics NeurIPS 2021 Probabilistic Margins for Instance Reweighting in Adversarial Training NeurIPS 2021 Provable Robustness of Adversarial Training for Learning Halfspaces with Noise ICML 2021 Provably Secure Federated Learning against Malicious Clients AAAI 2021 Query Complexity of Adversarial Attacks ICML 2021 Random Noise Defense Against Query-Based Black-Box Attacks NeurIPS 2021