Contingency-constrained economic dispatch with safe reinforcement learning. - Michael Eichelbeck; Hannah Markgraf; Matthias Althoff (ICMLA, 2022)

Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking. - Roland Stolz; Hanna Krasowski; Jakob Thumm; Michael Eichelbeck; Philipp Gassert; Matthias Althoff (NeurIPS, 2024)

CommonPower: Supercharging Machine Learning for Smart Grids. - Michael Eichelbeck; Hannah Markgraf; Matthias Althoff (CoRR, 2024)

Predicting building types and functions at transnational scale. - Jonas Fill; Michael Eichelbeck; Michael Ebner (CoRR, 2024)

Wind Turbine Fault Classification Based on Reconstruction Errors of SCADA Data. - Michael Eichelbeck; Max Adam; Kenneth Laureys; Milena Zurmühl; Matthias Althoff (e-Energy, 2025)

e-SparX: A Graph-Based Artifact Exchange Platform to Accelerate Machine Learning Research in the Energy Systems Community. - Annika Schneider; Lukas Schüttler; Jan Marco Ruiz de Vargas; Michael Eichelbeck; Christoph Goebel (e-Energy, 2025)

Formal Verification of Graph Convolutional Networks with Uncertain Node Features and Uncertain Graph Structure. - Tobias Ladner; Michael Eichelbeck; Matthias Althoff (Trans. Mach. Learn. Res., 2025)

PyTupli: A Scalable Infrastructure for Collaborative Offline Reinforcement Learning Projects. - Hannah Markgraf; Michael Eichelbeck; Daria Cappey; Selin Demirtürk; Yara Schattschneider; Matthias Althoff (CoRR, 2025)