dongyin92 / adversarially-robust-generalizationLinks
This repo contains the code for the experiments in "Rademacher Complexity for Adversarially Robust Generalization"
☆9Updated 6 years ago
Alternatives and similar repositories for adversarially-robust-generalization
Users that are interested in adversarially-robust-generalization are comparing it to the libraries listed below
Sorting:
- Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)☆45Updated 7 years ago
- can calculate the Hessian matrix and/or its spectrum for simple neural nets☆10Updated 7 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 3 years ago
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 5 years ago
- Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).☆23Updated 2 years ago
- Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."☆34Updated 6 years ago
- Scaleable input gradient regularization☆22Updated 5 years ago
- ☆58Updated 2 years ago
- Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf☆142Updated 5 years ago
- [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.☆26Updated 10 months ago
- ☆19Updated 5 years ago
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Updated 4 years ago
- Zeroth-order Min-max Optimization☆11Updated 4 years ago
- Implementation of Minimax Pareto Fairness framework☆21Updated 4 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆32Updated 4 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago
- Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network☆62Updated 5 years ago
- Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians (ICML 2019)☆17Updated 6 years ago
- ☆37Updated 4 years ago
- Implementation of Confidence-Calibrated Adversarial Training (CCAT).☆45Updated 4 years ago
- ☆87Updated 10 months ago
- The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size☆17Updated 6 years ago
- ☆50Updated 2 years ago
- Code for the paper "Adversarial Neural Pruning with Latent Vulnerability Suppression"☆15Updated 2 years ago
- [ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation☆54Updated last week
- Tilted Empirical Risk Minimization (ICLR '21)☆59Updated last year
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆49Updated 3 years ago
- Adversarial Defense for Ensemble Models (ICML 2019)☆61Updated 4 years ago
- MACER: MAximizing CErtified Radius (ICLR 2020)☆30Updated 5 years ago
- Code for "Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent" (ICML 2020 - Lifelong Learning Workshop)☆42Updated 2 years ago