thudzj / ScalableBDLLinks
Code for "BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayeisan Fine-tuning"
☆32Updated last year
Alternatives and similar repositories for ScalableBDL
Users that are interested in ScalableBDL are comparing it to the libraries listed below
Sorting:
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆36Updated 4 years ago
- ☆37Updated 4 years ago
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆20Updated 2 years ago
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 5 years ago
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆48Updated 3 years ago
- ☆49Updated 2 years ago
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆47Updated 3 years ago
- Learning Representations that Support Robust Transfer of Predictors☆20Updated 3 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).☆51Updated 4 years ago
- A Closer Look at Accuracy vs. Robustness☆88Updated 4 years ago
- CVPR'19 experiments with (on-manifold) adversarial examples.☆45Updated 5 years ago
- Implementation of Confidence-Calibrated Adversarial Training (CCAT).☆45Updated 5 years ago
- Code for the paper "Understanding Generalization through Visualizations"☆64Updated 4 years ago
- ☆35Updated 4 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 3 years ago
- ☆44Updated 6 months ago
- ☆23Updated 3 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆24Updated 3 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 3 years ago
- Pytorch implementation of regularization methods for deep networks obtained via kernel methods.☆22Updated 5 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆122Updated 3 years ago
- A Self-Consistent Robust Error (ICML 2022)☆69Updated 2 years ago
- Code for the paper "SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness" (NeurIPS 2021)☆21Updated 3 years ago
- Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…☆68Updated 3 years ago
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆44Updated 3 years ago
- [NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang☆114Updated 3 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 6 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 4 years ago
- ☆55Updated 5 years ago