Author

C. Goebel

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Preprint Sep 2026

Learning Control Policies from Heterogeneous Multi-Horizon Time Series in Battery Energy Management Systems

This paper introduces Representation-to-Decision (R2D), an end-to-end imitation learning framework that maps heterogeneous multi-horizon time-series inputs directly to battery control decisions through modular Temporal Feature Extractors (TFEs) and a shared latent representation, without an explicit load and PV forecas...

Sheng Yin, Vivek Teja Tanjavooru, Holger Hesse et al. · 0 citations

#machine learning Preprint Apr 2026

Neural Parameter Estimation of RC Thermal Building Models for Model Predictive Control

The Pretrained Estimator is proposed, a novel neural parameter estimation approach that embeds the physical equations into a neural network's training process to estimate RC parameters and achieves the best prediction performance among all RC-based methods and yields the lowest and least variable MPC costs across build...

F. Raisch, T. Germann, Sang-woo Ham et al. · 3 citations