Heterogeneous Knowledge for Augmented Modular Reinforcement Learning

no code implementations • 1 Jun 2023 • Lorenz Wolf, Mirco Musolesi

Existing modular Reinforcement Learning (RL) architectures are generally based on reusable components, also allowing for ``plug-and-play'' integration.

Decision Making reinforcement-learning +1

Energy-Based Models for Functional Data using Path Measure Tilting

1 code implementation • 4 Feb 2022 • Jen Ning Lim, Sebastian Vollmer, Lorenz Wolf, Andrew Duncan

Their ability to incorporate domain-specific choices and constraints into the structure of the model through composition make EBMs an appealing candidate for applications in physics, biology and computer vision and various other fields.