Predictability of Power Grid Frequency. - Johannes Kruse 001; Benjamin Schäfer 001; Dirk Witthaut (IEEE Access, 2020)

Exploring deterministic frequency deviations with explainable AI. - Johannes Kruse 001; Benjamin Schäfer 001; Dirk Witthaut (SmartGridComm, 2021)

Secondary control activation analysed and predicted with explainable AI. - Johannes Kruse 001; Benjamin Schäfer 001; Dirk Witthaut (CoRR, 2021)

Revealing drivers and risks for power grid frequency stability with explainable AI. - Johannes Kruse 001; Benjamin Schäfer 001; Dirk Witthaut (Patterns, 2021)

Predicting Dynamic Stability from Static Features in Power Grid Models using Machine Learning. - Maurizio Titz; Franz Kaiser; Johannes Kruse 001; Dirk Witthaut (CoRR, 2022)

Physics-inspired machine learning for power grid frequency modelling. - Johannes Kruse 001; Eike Cramer; Benjamin Schäfer 001; Dirk Witthaut (CoRR, 2022)

Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI. - Sebastian Pütz; Benjamin Schäfer 001; Dirk Witthaut; Johannes Kruse 001 (Energy Inform., 2022)

Regulatory Changes in German and Austrian Power Systems Explored with Explainable Artificial Intelligence. - Sebastian Pütz; Johannes Kruse 001; Dirk Witthaut; Veit Hagenmeyer; Benjamin Schäfer 001 (e-Energy (Companion), 2023)

NORMalize: The First Workshop on Normative Design and Evaluation of Recommender Systems. - Sanne Vrijenhoek; Lien Michiels; Johannes Kruse 001; Alain Starke; Nava Tintarev; Jordi Viader Guerrero (RecSys, 2023)

Regulatory Changes in Power Systems Explored with Explainable Artificial Intelligence. - Sebastian Pütz; Johannes Kruse 001; Dirk Witthaut; Veit Hagenmeyer; Benjamin Schäfer 001 (CoRR, 2023)

Machine learning of power grid frequency dynamics and control: prediction, explanation and stochastic modelling - Johannes Kruse 001 (2023)