6 citations · 6 across the 6 of their papers we have counts for
4 papers · 1 filter
Elign: Equivariant Diffusion Model Alignment from Foundational Machine Learning Force Fields
Yunyang Li, Lin Huang, Luojia Xia +2
Generative models for 3D molecular conformations must respect Euclidean symmetries and concentrate probability mass on thermodynamically favorable, mechanically stable structures.…
E2Former-V2: On-the-Fly Equivariant Attention with Linear Activation Memory
Lin Huang, Chengxiang Huang, Ziang Wang +7
Equivariant Graph Neural Networks (EGNNs) have become a widely used approach for modeling 3D atomistic systems. However, mainstream architectures face critical scalability bottlene…
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity
Erpai Luo, Xinran Wei, Lin Huang +7
Hamiltonian matrix prediction is pivotal in computational chemistry, serving as the foundation for determining a wide range of molecular properties. While SE(3) equivariant graph n…
E2Former: An Efficient and Equivariant Transformer with Linear-Scaling Tensor Products
Yunyang Li, Lin Huang, Zhihao Ding +10
Equivariant Graph Neural Networks (EGNNs) have demonstrated significant success in modeling microscale systems, including those in chemistry, biology and materials science. However…