34 citations · 71 across the 8 of their papers we have counts for
4 papers · 1 filter
FoMo Rewards: Can we cast foundation models as reward functions?
Ekdeep Singh Lubana, Johann Brehmer, Pim de Haan +1
We explore the viability of casting foundation models as generic reward functions for reinforcement learning. To this end, we propose a simple pipeline that interfaces an off-the-s…
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems
Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi +7
Recent advances in computational modelling of atomic systems, spanning molecules, proteins, and materials, represent them as geometric graphs with atoms embedded as nodes in 3D Euc…
Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers
Pim de Haan, Taco Cohen, Johann Brehmer
The Geometric Algebra Transformer (GATr) is a versatile architecture for geometric deep learning based on projective geometric algebra. We generalize this architecture into a bluep…
Information-driven Affordance Discovery for Efficient Robotic Manipulation
Pietro Mazzaglia, Taco Cohen, Daniel Dijkman
Robotic affordances, providing information about what actions can be taken in a given situation, can aid robotic manipulation. However, learning about affordances requires expensiv…