249 citations · 255 across the 4 of their papers we have counts for
4 papers
EquiformerV3: Scaling Efficient, Expressive, and General SE(3)-Equivariant Graph Attention Transformers
Yi-Lun Liao, Alexander J. Hoffman, Sabrina C. Shen +3
As -equivariant graph neural networks mature as a core tool for 3D atomistic modeling, improving their efficiency, expressivity, and physical consistency has become a centra…
Cross Learning between Electronic Structure Theories for Unifying Molecular, Surface, and Inorganic Crystal Foundation Force Fields
Ilyes Batatia, Chen Lin, Joseph Hart +5
Creating a single unified interatomic potential capable of attaining ab initio accuracy across all chemistry remains a long-standing challenge in computational chemistry and materi…
Zero Shot Molecular Generation via Similarity Kernels
Rokas Elijošius, Fabian Zills, Ilyes Batatia +4
Generative modelling aims to accelerate the discovery of novel chemicals by directly proposing structures with desirable properties. Recently, score-based, or diffusion, generative…
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…