BaoWangMath / EnResNet
☆19Updated 5 years ago
Alternatives and similar repositories for EnResNet:
Users that are interested in EnResNet are comparing it to the libraries listed below
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Updated 4 years ago
- ☆19Updated 4 years ago
- CVPR'19 experiments with (on-manifold) adversarial examples.☆44Updated 5 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆55Updated 3 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆35Updated 4 years ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- Code for "Bridging the Gap between f-GANs and Wasserstein GANs", ICML 2020☆14Updated 4 years ago
- [ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“☆24Updated 3 years ago
- Code base for SRSGD.☆28Updated 5 years ago
- ☆10Updated 7 months ago
- Scaleable input gradient regularization☆22Updated 5 years ago
- ☆10Updated 5 years ago
- Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out☆27Updated 3 years ago
- Official adversarial mixup resynthesis repository☆35Updated 5 years ago
- The code for the paper: https://arxiv.org/pdf/1802.00168.pdf☆17Updated 5 years ago
- Code for the paper "Understanding Generalization through Visualizations"☆60Updated 4 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- ☆20Updated 4 years ago
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 4 years ago
- ☆20Updated 7 months ago
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆35Updated 3 years ago
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)☆34Updated 7 years ago
- This repo contains the code used for NeurIPS 2019 paper "Asymmetric Valleys: Beyond Sharp and Flat Local Minima".☆14Updated 5 years ago
- Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"☆22Updated 3 years ago
- Generator loss to reduce mode-collapse and to improve the generated samples quality.☆34Updated 5 years ago
- Code accompanying our paper "Finding trainable sparse networks through Neural Tangent Transfer" to be published at ICML-2020.☆13Updated 4 years ago
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆43Updated 3 years ago
- ☆10Updated 4 years ago