Michael Eichelbeck

According to our database, Michael Eichelbeck authored at least 13 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

To Learn or Not to Learn: A Litmus Test for Using Reinforcement Learning in Control.

Victor Schulte, Michael Eichelbeck, Matthias Althoff

CoRR, April, 2026

CommonPower: A Framework for Safe Data-Driven Smart Grid Control.

Michael Eichelbeck, Hannah Markgraf, Matthias Althoff

IEEE Trans. Smart Grid, January, 2026

BSAT: B-Spline Adaptive Tokenizer for Long-Term Time Series Forecasting.

Maximilian Reinwardt, Michael Eichelbeck, Matthias Althoff

CoRR, January, 2026

Predicting Building Types and Functions at Transnational Scale.

Jonas Fill, Michael Eichelbeck, Michael Ebner

IEEE Access, 2026

Improving Stochastic Action-Constrained Reinforcement Learning via Truncated Distributions.

Roland Stolz, Michael Eichelbeck, Matthias Althoff

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

PyTupli: A Scalable Infrastructure for Collaborative Offline Reinforcement Learning Projects.

Hannah Markgraf, Michael Eichelbeck, Daria Cappey, Selin Demirtürk, Yara Schattschneider, Matthias Althoff

CoRR, May, 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

Zono-Conformal Prediction: Zonotope-Based Uncertainty Quantification for Regression and Classification Tasks.

Laura Lützow, Michael Eichelbeck, Mykel J. Kochenderfer, Matthias Althoff

J. Mach. Learn. Res., 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

Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems, 2025

Wind Turbine Fault Classification Based on Reconstruction Errors of SCADA Data.

Michael Eichelbeck, Max Adam, Kenneth Laureys, Milena Zurmühl, Matthias Althoff

Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems, 2025

2024

CommonPower: Supercharging Machine Learning for Smart Grids.

Michael Eichelbeck, Hannah Markgraf, Matthias Althoff

CoRR, 2024

Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking.

Roland Stolz, Hanna Krasowski, Jakob Thumm, Michael Eichelbeck, Philipp Gassert, Matthias Althoff

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2022

Contingency-constrained economic dispatch with safe reinforcement learning.

Michael Eichelbeck, Hannah Markgraf, Matthias Althoff

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022