David R. Wessels

According to our database, David R. Wessels authored at least 6 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Uncertainty-aware Machine Learning Interatomic Potentials via Learned Functional Perturbations.

Olga Zaghen, Maksim Zhdanov, Dario Coscia, David R. Wessels, Erik J. Bekkers

CoRR, May, 2026

2025

Platonic Transformers: A Solid Choice For Equivariance.

Mohammad Mohaiminul Islam, Rishabh Anand, David R. Wessels, Friso de Kruiff, Thijs P. Kuipers, Rex Ying, Clara I. Sánchez, Sharvaree Vadgama, Georg Bökman, Erik J. Bekkers

CoRR, October, 2025

Equivariant Eikonal Neural Networks: Grid-Free, Scalable Travel-Time Prediction on Homogeneous Spaces.

Alejandro García-Castellanos, David R. Wessels, Nicky J. van den Berg, Remco Duits, Daniël M. Pelt, Erik J. Bekkers

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Grounding Continuous Representations in Geometry: Equivariant Neural Fields.

David R. Wessels, David M. Knigge, Riccardo Valperga, Samuele Papa, Sharvaree P. Vadgama, Efstratios Gavves, Erik J. Bekkers

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Space-Time Continuous PDE Forecasting using Equivariant Neural Fields.

David M. Knigge, David R. Wessels, Riccardo Valperga, Samuele Papa, Jan-Jakob Sonke, Erik J. Bekkers, Efstratios Gavves

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

The NGT200 Dataset: Geometric Multi-View Isolated Sign Recognition.

Oline Ranum, David R. Wessels, Gomer Otterspeer, Erik J. Bekkers, Floris Roelofsen, Jari I. Andersen

Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024, 2024