YunseokJANG / l2l-da
Repository for our ICCV 2019 paper: Adversarial Defense via Learning to Generate Diverse Attacks
☆21Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for l2l-da
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆99Updated 2 years ago
- CVPR'19 experiments with (on-manifold) adversarial examples.☆43Updated 4 years ago
- Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).☆26Updated 5 years ago
- Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks☆64Updated 5 years ago
- Code for NeurIPS 2019 Paper☆48Updated 4 years ago
- Official adversarial mixup resynthesis repository☆35Updated 4 years ago
- Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing the…☆54Updated last year
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆46Updated last year
- Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]☆18Updated 6 years ago
- ☆25Updated 5 years ago
- Analysis of Adversarial Logit Pairing☆60Updated 6 years ago
- Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.☆49Updated 5 years ago
- [ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation☆52Updated 2 months ago
- Implementation for What it Thinks is Important is Important: Robustness Transfers through Input Gradients (CVPR 2020 Oral)☆16Updated last year
- Source code for Learning Transferable Adversarial Examples via Ghost Networks (AAAI2020)☆59Updated 5 years ago
- Official repository for "Bridging Adversarial Robustness and Gradient Interpretability".☆30Updated 5 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆55Updated 3 years ago
- Further improve robustness of mixup-trained models in inference (ICLR 2020)☆60Updated 4 years ago
- Implementation for Jacobian Adversarially Regularized Networks for Robustness (ICLR 2020)☆21Updated 4 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆31Updated 4 years ago
- An Algorithm to Quantify Robustness of Recurrent Neural Networks☆46Updated 4 years ago
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)☆34Updated 6 years ago
- Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019☆59Updated 5 years ago
- ☆86Updated 3 months ago
- Logit Pairing Methods Can Fool Gradient-Based Attacks [NeurIPS 2018 Workshop on Security in Machine Learning]☆18Updated 5 years ago
- Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out☆27Updated 3 years ago
- Coupling rejection strategy against adversarial attacks (CVPR 2022)☆28Updated 2 years ago
- Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"☆23Updated 5 years ago
- Code Repository to check robustness of 3D Deep Learning (Volumetric and PointNet) to occlusion attacks☆13Updated 5 years ago
- Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength☆37Updated 4 years ago