jhjacobsen / fully-invertible-revnet
☆31Updated 4 years ago
Alternatives and similar repositories for fully-invertible-revnet:
Users that are interested in fully-invertible-revnet are comparing it to the libraries listed below
- ☆87Updated 7 months ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆34Updated 4 years ago
- Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).☆26Updated 5 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆32Updated 4 years ago
- ☆20Updated 7 months ago
- A way to achieve uniform confidence far away from the training data.☆37Updated 3 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.☆49Updated 5 years ago
- Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."☆34Updated 6 years ago
- A Closer Look at Accuracy vs. Robustness☆88Updated 3 years ago
- Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]☆18Updated 6 years ago
- ☆54Updated 4 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Code implementing the experiments described in the NeurIPS 2018 paper "With Friends Like These, Who Needs Adversaries?".☆13Updated 4 years ago
- [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.☆26Updated 7 months ago
- Code for "Robustness May Be at Odds with Accuracy"☆92Updated last year
- ☆58Updated last year
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆55Updated 3 years ago
- Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks☆65Updated 5 years ago
- Training vision models with full-batch gradient descent and regularization☆37Updated 2 years ago
- Pytorch implementation of regularization methods for deep networks obtained via kernel methods.☆22Updated 5 years ago
- Computing various measures and generalization bounds on convolutional and fully connected networks☆35Updated 6 years ago
- A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturb…☆11Updated 4 years ago
- CVPR'19 experiments with (on-manifold) adversarial examples.☆44Updated 5 years ago
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 2 years ago
- ☆89Updated 3 years ago
- Implementation of Confidence-Calibrated Adversarial Training (CCAT).☆45Updated 4 years ago
- Official adversarial mixup resynthesis repository☆35Updated 5 years ago
- Source code for the paper "Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness"☆25Updated 5 years ago
- Further improve robustness of mixup-trained models in inference (ICLR 2020)☆60Updated 4 years ago