2 papers
physics.comp-ph2026
Fast and Accurate Equivariant Foundation Models for Atomistic Simulation
Seán R. Kavanagh, Chuin Wei Tan, Menghang Wang +12
Machine-learned interatomic potentials (MLIPs) have emerged as a transformative tool for computational materials science and chemistry, with universal potentials trained on large a…
cs.LG2025
An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks
Vivek Bharadwaj, Austin Glover, Aydin Buluc +1
Rotation equivariant graph neural networks, i.e. networks designed to guarantee certain geometric relations between their inputs and outputs, yield state of the art performance on…