2 citations · 4 across the 4 of their papers we have counts for
Showing 2025 · physics.comp-phShow all
2 papers · 2 filters
physics.comp-ph2025★ 1 cited
Scalable Data-Driven Basis Selection for Linear Machine Learning Interatomic Potentials
Tina Torabi, Matthias Militzer, Michael P. Friedlander +1
Machine learning interatomic potentials (MLIPs) provide an effective approach for accurately and efficiently modeling atomic interactions, expanding the capabilities of atomistic s…
physics.comp-ph2025★ 1 cited
Fast automatically differentiable matrix functions and applications in molecular simulations
Tina Torabi, Timon S Gutleb, Christoph Ortner
We describe efficient differentiation methods for computing Jacobians and gradients of a large class of matrix functions including the matrix logarithm and -th roots $…