3.6k citations · 10.6k across the 54 of their papers we have counts for
3 papers · 1 filter
Force field optimization by end-to-end differentiable atomistic simulation
Abhijeet S. Gangan, Samuel S. Schoenholz, Ekin Dogus Cubuk +2
The accuracy of atomistic simulations depends on the precision of force fields. Traditional numerical methods often struggle to optimize the empirical force field parameters for re…
Generative Hierarchical Materials Search
Sherry Yang, Simon Batzner, Ruiqi Gao +7
Generative models trained at scale can now produce text, video, and more recently, scientific data such as crystal structures. In applications of generative approaches to materials…
Scaling (Down) CLIP: A Comprehensive Analysis of Data, Architecture, and Training Strategies
Zichao Li, Cihang Xie, Ekin Dogus Cubuk
This paper investigates the performance of the Contrastive Language-Image Pre-training (CLIP) when scaled down to limited computation budgets. We explore CLIP along three dimension…