adversarial robustness

Sequential Randomized Smoothing for Adversarially Robust Speech Recognition EMNLP 2021 Shape-Texture Debiased Neural Network Training ICLR 2021 Shift Invariance Can Reduce Adversarial Robustness NeurIPS 2021 Simpler Certified Radius Maximization by Propagating Covariances CVPR 2021 Skew Orthogonal Convolutions ICML 2021 SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation ICML 2021 Spectral Leakage and Rethinking the Kernel Size in CNNs ICCV 2021 StyleMix: Separating Content and Style for Enhanced Data Augmentation CVPR 2021 The curious case of adversarially robust models: More data can help, double descend, or hurt generalization UAI 2021 The Lipschitz Constant of Self-Attention ICML 2021 Tightening Robustness Verification of Convolutional Neural Networks with Fine-Grained Linear Approximation AAAI 2021 To be Robust or to be Fair: Towards Fairness in Adversarial Training ICML 2021 Token-Aware Virtual Adversarial Training in Natural Language Understanding AAAI 2021 Towards a more Robust Evaluation for Conversational Question Answering ACL 2021 Towards a Theoretical Understanding of the Robustness of Variational Autoencoders AISTATS 2021 Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons ICML 2021 Towards Defending against Adversarial Examples via Attack-Invariant Features ICML 2021 Towards Efficient and Effective Adversarial Training NeurIPS 2021 Towards Evaluating and Training Verifiably Robust Neural Networks CVPR 2021 Towards optimally abstaining from prediction with OOD test examples NeurIPS 2021 Towards Robustness Against Natural Language Word Substitutions ICLR 2021 Towards Robustness of Deep Neural Networks via Regularization ICCV 2021 Towards Robust Neural Networks via Close-loop Control ICLR 2021 Towards Stable and Robust AdderNets NeurIPS 2021 Towards Understanding the Generative Capability of Adversarially Robust Classifiers ICCV 2021