2 papers
cs.DC2025
Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE
Jesun Firoz, Franco Pellegrini, Mario Geiger +17
Chemistry Foundation Models (CFMs) that leverage Graph Neural Networks (GNNs) operating on 3D molecular graph structures are becoming indispensable tools for computational chemists…
cond-mat.mtrl-sci2024
Revealing the Evolution of Order in Materials Microstructures Using Multi-Modal Computer Vision
Arman Ter-Petrosyan, Michael Holden, Jenna A. Bilbrey +11
The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microst…