New presentation: Generative Machine Learning for Transition Metal Chemistry

Summary 

This talk gave an overview of the research done at the Hylleraas Center on the topic of Generative Machine Learning for Transition Metal Chemistry, including recent work on genetic algorithms and variational autoencoders, also reviewing related projects like the tmQM dataset, orbital-based graph representations, and deep learning models for the prediction of quantum properties, and thermodynamic and kinetic parameters. 

Time and place of the conference

May 20, 2024 at Los Alamos National Lab (USA) and virtual.

For more information 

Refer to the website: https://mlcm-24.github.io/