203 citations · 736 across the 19 of their papers we have counts for
3 papers · 1 filter
Walrus: A Cross-Domain Foundation Model for Continuum Dynamics
Michael McCabe, Payel Mukhopadhyay, Tanya Marwah +22
Foundation models have transformed machine learning for language and vision, but achieving comparable impact in physical simulation remains a challenge. Data heterogeneity and unst…
Equivariant geometric convolutions for emulation of dynamical systems
Wilson G. Gregory, David W. Hogg, Ben Blum-Smith +3
Machine learning methods are increasingly being employed as surrogate models in place of computationally expensive and slow numerical integrators for a bevy of applications in the…
The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence
Francisco Villaescusa-Navarro, Shy Genel, Daniel Angles-Alcazar +25
We present the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) Multifield Dataset, CMD, a collection of hundreds of thousands of 2D maps and 3D grids containi…