11 citations · 24 across the 13 of their papers we have counts for
3 papers · 1 filter
Admissable: Training Reinforcement Learning Agents against Adversarial Missingness
Paul Stahlhofen, Luca Hermes, Tim Kochs +2
In order to make Reinforcement Learning algorithms applicable in real world scenarios, safety must be ensured even under adverse operating conditions. In this work, we consider the…
MeGA-MP: Metric Graph Advection Message Passing -- A Physics-Informed Message Passing Operator for Advection-Dominated Metric Graphs
Janine Strotherm, Luca Hermes, André Artelt +1
Many real-world systems are organized as networks where spatio-temporal dynamics unfold along connections and not discretely between nodes. Examples include utility networks such a…
DGPO: RL-Steered Graph Diffusion for Neural Architecture Generation
Aleksei Liuliakov, Luca Hermes, Barbara Hammer
Reinforcement learning fine-tuning has proven effective for steering generative diffusion models toward desired properties in image and molecular domains. Graph diffusion models ha…