Yuan-En Sun

A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules

Graph neural networks (GNNs) -- learn graph representations by exploiting the graph's sparsity, connectivity, and symmetries -- have become indispensable for learning geometric data like molecules. However, the most used graphs (e.g., radial cutoff graphs) in molecular modeling lack theoretical guar…