Haiyang Yu

Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory

A Two-Phase Deep Learning Framework for Adaptive Time-Stepping in High-Speed Flow Modeling

Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames

Empowering GNNs for Domain Adaptation via Denoising Target Graph

On Explaining Equivariant Graph Networks via Improved Relevance Propagation

Learning to Discover Regulatory Elements for Gene Expression Prediction

Tensor Decomposition Networks for Accelerating Machine Learning Force Field Computations

Learning Time-Dependent Density Functional Theory via Geometry and Physics Aware Latent Evolution

Spectro-Riemannian Graph Neural Networks

On Explaining Equivariant Graph Networks via Improved Relevance Propagation