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cs.LG2026
Drift Localization using Conformal Predictions
Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf +1
Concept drift -- the change of the distribution over time -- poses significant challenges for learning systems and is of central interest for monitoring. Understanding drift is thu…
cs.LG2026
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…
cs.LG2024
Koopman-Based Surrogate Modelling of Turbulent Rayleigh-Bénard Convection
Thorben Markmann, Michiel Straat, Barbara Hammer
Several related works have introduced Koopman-based Machine Learning architectures as a surrogate model for dynamical systems. These architectures aim to learn non-linear measureme…