203 citations · 389 across the 9 of their papers we have counts for
3 papers · 1 filter
Equivariant Graph Neural Networks for 3D Macromolecular Structure
Bowen Jing, Stephan Eismann, Pratham N. Soni +1
Representing and reasoning about 3D structures of macromolecules is emerging as a distinct challenge in machine learning. Here, we extend recent work on geometric vector perceptron…
ATOM3D: Tasks On Molecules in Three Dimensions
Raphael J. L. Townshend, Martin Vögele, Patricia Suriana +10
Computational methods that operate on three-dimensional molecular structure have the potential to solve important questions in biology and chemistry. In particular, deep neural net…
Geometric Prediction: Moving Beyond Scalars
Raphael J. L. Townshend, Brent Townshend, Stephan Eismann +1
Many quantities we are interested in predicting are geometric tensors; we refer to this class of problems as geometric prediction. Attempts to perform geometric prediction in real-…