22 citations · 28 across the 3 of their papers we have counts for
3 papers
cond-mat.mtrl-sci2023★ 1 cited
Spectroscopy-Guided Discovery of Three-Dimensional Structures of Disordered Materials with Diffusion Models
Hyuna Kwon, Tim Hsu, Wenyu Sun +8
The ability to rapidly develop materials with desired properties has a transformative impact on a broad range of emerging technologies. In this work, we introduce a new framework b…
cond-mat.dis-nn2022★ 22 cited
Quantifying Disorder One Atom at a Time Using an Interpretable Graph Neural Network Paradigm
James Chapman, Tim Hsu, Xiao Chen +2
Quantifying the level of atomic disorder within materials is critical to understanding how evolving local structural environments dictate performance and durability. Here, we lever…
cs.LG2021★ 5 cited
Efficient, Interpretable Graph Neural Network Representation for Angle-dependent Properties and its Application to Optical Spectroscopy
Tim Hsu, Tuan Anh Pham, Nathan Keilbart +6
Graph neural networks are attractive for learning properties of atomic structures thanks to their intuitive graph encoding of atoms and bonds. However, conventional encoding does n…