Distributionally robust neural networks for group shifts

Group-conditional DRO to alleviate spurious correlations

Fairness toolkit for pytorch, scikit learn and autogluon

A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.

Mechanistically interpretable neurosymbolic AI (Nature Comput Sci 2024): losslessly compressing NNs to computer code and discovering new algorithms which generalize out-of-distribution and outperfo…

A framework to optimize Parameter-Efficient Fine-Tuning for Fairness in Medical Image Analysis

[ICLR 2023 spotlight] MEDFAIR: Benchmarking Fairness for Medical Imaging

Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated Uncertainty

repository for autoPET machine lerning challenge

ReactJS app