5 citations · 6 across the 4 of their papers we have counts for
5 papers · 1 filter
Efficient Reasoning on the Edge
Yelysei Bondarenko, Thomas Hehn, Rob Hesselink +15
Large language models (LLMs) with chain-of-thought reasoning achieve state-of-the-art performance across complex problem-solving tasks, but their verbose reasoning traces and large…
Fast, Expressive SE Equivariant Networks through Weight-Sharing in Position-Orientation Space
Erik J Bekkers, Sharvaree Vadgama, Rob D Hesselink +2
Based on the theory of homogeneous spaces we derive geometrically optimal edge attributes to be used within the flexible message-passing framework. We formalize the notion of weigh…
E(n) Equivariant Message Passing Simplicial Networks
Floor Eijkelboom, Rob Hesselink, Erik Bekkers
This paper presents Equivariant Message Passing Simplicial Networks (EMPSNs), a novel approach to learning on geometric graphs and point clouds that is equivariant…
Geometric and Physical Quantities Improve E(3) Equivariant Message Passing
Johannes Brandstetter, Rob Hesselink, Elise van der Pol +2
Including covariant information, such as position, force, velocity or spin is important in many tasks in computational physics and chemistry. We introduce Steerable E(3) Equivarian…
Latent Transformations for Discrete-Data Normalising Flows
Rob Hesselink, Wilker Aziz
Normalising flows (NFs) for discrete data are challenging because parameterising bijective transformations of discrete variables requires predicting discrete/integer parameters. Ha…