Search Results for author: Erik J Bekkers

Found 2 papers, 2 papers with code

Fast, Expressive SE$(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space

1 code implementation4 Oct 2023 Erik J Bekkers, Sharvaree Vadgama, Rob D Hesselink, Putri A van der Linden, David W Romero

The theory of homogeneous spaces tells us how to do group convolutions with feature maps over the homogeneous space of positions $\mathbb{R}^3$, position and orientations $\mathbb{R}^3 {\times} S^2$, and the group $SE(3)$ itself.

Computational Efficiency Position +1

Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

2 code implementations ICLR 2022 Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J Bekkers, Max Welling

Including covariant information, such as position, force, velocity or spin is important in many tasks in computational physics and chemistry.

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