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Found 4 papers, 1 papers with code
Privacy-preserving data release leveraging optimal transport and particle gradient descent
We present a novel approach for differentially private data synthesis of protected tabular datasets, a relevant task in highly sensitive domains such as healthcare and government.
Interpretable Distribution Shift Detection using Optimal Transport
We propose a method to identify and characterize distribution shifts in classification datasets based on optimal transport.
Predicting Out-of-Domain Generalization with Neighborhood Invariance
Developing and deploying machine learning models safely depends on the ability to characterize and compare their abilities to generalize to new environments.
GAN-based Data Augmentation for Chest X-ray Classification
A common problem in computer vision -- particularly in medical applications -- is a lack of sufficiently diverse, large sets of training data.
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