adversarial example

Classification with Rejection: Scaling Generative Classifiers with Supervised Deep Infomax IJCAI 2020 CoachGAN WACV 2020 Compositional Explanations of Neurons NeurIPS 2020 Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks ICML 2020 Contrastive Learning with Adversarial Examples NeurIPS 2020 Defending Against Physically Realizable Attacks on Image Classification ICLR 2020 Denoised Smoothing: A Provable Defense for Pretrained Classifiers NeurIPS 2020 DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking ACL 2020 Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors CVPR 2020 Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions ICLR 2020 Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks ICML 2020 Efficient Adversarial Training With Transferable Adversarial Examples CVPR 2020 Enhancing Adversarial Defense by k-Winners-Take-All ICLR 2020 Enhancing Cross-Task Black-Box Transferability of Adversarial Examples With Dispersion Reduction CVPR 2020 Evade Deep Image Retrieval by Stashing Private Images in the Hash Space CVPR 2020 Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples ACL 2020 Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking ICLR 2020 Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations ICML 2020 Generalization to Mitigate Synonym Substitution Attacks EMNLP 2020 Generate (Non-Software) Bugs to Fool Classifiers AAAI 2020 Generating Adversarial Examples for Holding Robustness of Source Code Processing Models AAAI 2020 Generating Robust Audio Adversarial Examples with Temporal Dependency IJCAI 2020 GeoDA: A Geometric Framework for Black-Box Adversarial Attacks CVPR 2020 Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data JMLR 2020 Group-Wise Dynamic Dropout Based on Latent Semantic Variations AAAI 2020