microsoft / robustdgLinks
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
☆176Updated last year
Alternatives and similar repositories for robustdg
Users that are interested in robustdg are comparing it to the libraries listed below
Sorting:
- Official implementation of paper Gradient Matching for Domain Generalization☆122Updated 3 years ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆87Updated 3 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆89Updated 5 years ago
- ☆63Updated 4 years ago
- ☆37Updated 4 years ago
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆72Updated last year
- Robust Out-of-distribution Detection in Neural Networks☆73Updated 3 years ago
- Generalizing to unseen domains via distribution matching☆72Updated 4 years ago
- Official code for the paper "Task2Vec: Task Embedding for Meta-Learning" (https://arxiv.org/abs/1902.03545, ICCV 2019)☆122Updated 2 years ago
- ☆36Updated 4 years ago
- This repository contains the code of the distribution shift framework presented in A Fine-Grained Analysis on Distribution Shift (Wiles e…☆83Updated last month
- Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…☆53Updated 4 years ago
- ☆66Updated 5 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 4 years ago
- Implementation of 'DIVA: Domain Invariant Variational Autoencoders'☆103Updated 5 years ago
- Code for the paper Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift☆38Updated 4 years ago
- We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…☆57Updated 3 years ago
- A way to achieve uniform confidence far away from the training data.☆38Updated 4 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- Description Code for the paper "Robust Inference via Generative Classifiers for Handling Noisy Labels".☆33Updated 5 years ago
- Tilted Empirical Risk Minimization (ICLR '21)☆60Updated last year
- Coresets via Bilevel Optimization☆66Updated 4 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆50Updated 4 years ago
- ☆84Updated last year
- Distributionally robust neural networks for group shifts☆273Updated 2 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- ☆108Updated last year
- Regularized Learning under label shifts☆18Updated 6 years ago
- Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)☆99Updated 3 years ago
- Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)☆91Updated 4 years ago