Min Wu

Pathway Activity Autoencoders reveal that integrating multi-omics data can significantly enhance cancer risk stratification and survival predictions while maintaining interpretability.

Training machine learning models directly on encrypted data is now provably convergent, private, and more efficient thanks to a novel approach that avoids costly per-sample gradient clipping.