Distributed model predictive control of a nonlinear building energy system using consensus ADMM. - Steffen Eser; Phillip Stoffel; Alexander Kümpel; Dirk Müller 005 (MED, 2022)

Combining Data-driven and Physics-based Process Models for Hybrid Model Predictive Control of Building Energy Systems. - Phillip Stoffel; Charlotte Löffler; Steffen Eser; Alexander Kümpel; Dirk Müller 005 (MED, 2022)

Toward Trustworthy Machine Learning Models for Fault Detection in Energy Systems. - Martin Rätz; Patrick Henkel; Phillip Stoffel; Rita Streblow; Dirk Müller 005 (BuildSys, 2023)

Interpretable data-driven model predictive control of building energy systems using SHAP. - Patrick Henkel; Tobias Kasperski; Phillip Stoffel; Dirk Müller 005 (L4DC, 2024)