An overview of Los Alamos National Laboratory and the Theoretical Division.
A closed-form mathematical framework for modeling turbulent fluids
Robust Training of Machine Learning Interatomic Potentials with Dimensionality Reduction and Stratified Sampling
CHGNet: pretrained universal interatomic potential to study electron coupled ionic systems
Supercomputing at the exascale and beyond: future trends and challenges
Multi-scale modeling of the evolution of structure and properties in materials for nuclear energy applications
Gradient-Based Multidisciplinary Design Optimization for Propeller Design | Validation of a multivariate non-Gaussian, non-stationary wind pressure simulation model for performance-based wind engineering
Efficient calculations of electronic structures with machine-learning models
The U-M Data Science and AI Summit is the largest annual data science and AI event on campus. This event brings together the U-M data science and AI research community and their external collaborators to build research vision and collaboration. It also showcases the breadth and depth of U-M data science and AI research, from […]
The U-M Data Science and AI Summit is the largest annual data science and AI event on campus. This event brings together the U-M data science and AI research community and their external collaborators to build research vision and collaboration. It also showcases the breadth and depth of U-M data science and AI research, from […]