Geometric Representation Condition Improves Equivariant Molecule Generation
Recent advancements in molecular generative models have demonstrated substantial
potential in accelerating scientific discovery, particularly in drug design. However, these …
potential in accelerating scientific discovery, particularly in drug design. However, these …
Weisfeiler Leman for Euclidean Equivariant Machine Learning
The $ k $-Weifeiler-Leman ($ k $-WL) graph isomorphism test hierarchy is a common
method for assessing the expressive power of graph neural networks (GNNs). Recently, the …
method for assessing the expressive power of graph neural networks (GNNs). Recently, the …
On the Expressive Power of Sparse Geometric MPNNs
Motivated by applications in chemistry and other sciences, we study the expressive power of
message-passing neural networks for geometric graphs, whose node features correspond to …
message-passing neural networks for geometric graphs, whose node features correspond to …