249 citations · 408 across the 15 of their papers we have counts for
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stat.ML2023
A Geometric Insight into Equivariant Message Passing Neural Networks on Riemannian Manifolds
Ilyes Batatia
This work proposes a geometric insight into equivariant message passing on Riemannian manifolds. As previously proposed, numerical features on Riemannian manifolds are represented…
stat.ML2023
Equivariant Matrix Function Neural Networks
Ilyes Batatia, Lars L. Schaaf, Huajie Chen +3
Graph Neural Networks (GNNs), especially message-passing neural networks (MPNNs), have emerged as powerful architectures for learning on graphs in diverse applications. However, MP…
stat.ML2023★ 2 cited
A General Framework for Equivariant Neural Networks on Reductive Lie Groups
Ilyes Batatia, Mario Geiger, Jose Munoz +3
Reductive Lie Groups, such as the orthogonal groups, the Lorentz group, or the unitary groups, play essential roles across scientific fields as diverse as high energy physics, quan…