JonasGeiping / dataaugsLinks
☆18Updated 2 years ago
Alternatives and similar repositories for dataaugs
Users that are interested in dataaugs are comparing it to the libraries listed below
Sorting:
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated 2 years ago
- ☆55Updated 5 years ago
- ☆38Updated 4 years ago
- Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)☆28Updated 4 years ago
- Code for the paper "Data Feedback Loops: Model-driven Amplification of Dataset Biases"☆16Updated 3 years ago
- Data for "Datamodels: Predicting Predictions with Training Data"☆97Updated 2 years ago
- DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization☆31Updated 2 years ago
- ☆26Updated 3 years ago
- ☆34Updated 3 months ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 3 years ago
- ☆46Updated 2 years ago
- ☆95Updated 2 years ago
- ModelDiff: A Framework for Comparing Learning Algorithms☆59Updated 2 years ago
- Distilling Model Failures as Directions in Latent Space☆47Updated 2 years ago
- ☆34Updated last year
- Training vision models with full-batch gradient descent and regularization☆37Updated 2 years ago
- Learning perturbation sets for robust machine learning☆65Updated 4 years ago
- Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)☆25Updated 2 years ago
- Host CIFAR-10.2 Data Set☆13Updated 3 years ago
- Understanding Rare Spurious Correlations in Neural Network☆12Updated 3 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆24Updated 3 years ago
- ☆37Updated last year
- Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation☆45Updated 2 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆57Updated 4 years ago
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆19Updated 2 years ago
- Code for paper "Can contrastive learning avoid shortcut solutions?" NeurIPS 2021.☆47Updated 3 years ago
- ☆58Updated 2 years ago
- Code for the ICLR 2020 Paper, "A Theory of Usable Information under Computational Constraints"☆26Updated 5 years ago
- ☆108Updated last year
- ☆25Updated 5 years ago