Bai-Li / STN-CodeLinks
Code for Stability Training with Noise (STN)
☆22Updated 4 years ago
Alternatives and similar repositories for STN-Code
Users that are interested in STN-Code are comparing it to the libraries listed below
Sorting:
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 2 years ago
- Interval attacks (adversarial ML)☆21Updated 6 years ago
- Benchmark for LP-relaxed robustness verification of ReLU-networks☆41Updated 6 years ago
- ☆48Updated 4 years ago
- code we used in Decision Boundary Analysis of Adversarial Examples https://openreview.net/forum?id=BkpiPMbA-☆28Updated 6 years ago
- Code for FAB-attack☆33Updated 5 years ago
- Code for "Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors"☆64Updated 5 years ago
- Feature Scattering Adversarial Training (NeurIPS19)☆74Updated last year
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆32Updated 5 years ago
- Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs☆97Updated 4 years ago
- Analysis of Adversarial Logit Pairing☆60Updated 7 years ago
- Official TensorFlow implementation of "Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization" (ICML 2019)☆40Updated 4 years ago
- Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".☆55Updated 3 years ago
- AAAI 2019 oral presentation☆52Updated 2 months ago
- Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.☆49Updated 5 years ago
- ☆88Updated last year
- CROWN: A Neural Network Verification Framework for Networks with General Activation Functions☆38Updated 6 years ago
- Source code for the paper "Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness"☆25Updated 5 years ago
- Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength☆38Updated 5 years ago
- CLEVER (Cross-Lipschitz Extreme Value for nEtwork Robustness) is a robustness metric for deep neural networks☆62Updated 4 years ago
- ☆56Updated 2 years ago
- Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf☆142Updated 5 years ago
- ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks☆169Updated 4 years ago
- [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.☆26Updated last year
- StrAttack, ICLR 2019☆33Updated 6 years ago
- Adversarial Distributional Training (NeurIPS 2020)☆63Updated 4 years ago
- Implementation of Confidence-Calibrated Adversarial Training (CCAT).☆45Updated 5 years ago
- Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"☆23Updated 6 years ago
- Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTor…☆98Updated 4 years ago
- [CVPR'19] Trust Region Based Adversarial Attack☆20Updated 4 years ago