249 citations · 264 across the 3 of their papers we have counts for
3 papers
Design Space of Self--Consistent Electrostatic Machine Learning Interatomic Potentials
William J. Baldwin, Ilyes Batatia, Martin Vondrák +2
Machine learning interatomic potentials (MLIPs) have become widely used tools in atomistic simulations. For much of the history of this field, the most commonly employed architectu…
Efficient Composite Infrared Spectroscopy: Combining the Doubly-Harmonic Approximation with Machine Learning Potentials
Philipp Pracht, Yuthika Pillai, Venkat Kapil +5
Vibrational spectroscopy is a cornerstone technique for molecular characterization and offers an ideal target for the computational investigation of molecular materials. Building o…
A foundation model for atomistic materials chemistry
Ilyes Batatia, Philipp Benner, Yuan Chiang +85
Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much…