DeepHyper: Automated Deep Neural Networks Design Tool Argonne researchers develop a software package to automate critical neural network design.
DLHub: State-of-the-Art Publication, Discovery, and Indexing of Machine Learning Models Argonne has developed a state-of-the-art repository to collect, publish,and categorize models, making them easily accessible to others who want to use them.
CANDLE: Simulation-Enabled Precision Medicine for Cancer Argonne is leading a collaboration of DOE laboratories and the National Cancer Institute to address cancer research challenges.
Quantifying Energy Drivers in Chemical Separations Argonne researchers seek new approaches to low-energy chemical separations.
Deep Learning to Analyze Galaxy-scale Lensing Systems A team at Argonne is training a modular deep learning pipeline for denoising and deblending gravitational lensing systems.