Koopman operator dynamical models: Learning, analysis and control. - Petar Bevanda; Stefan Sosnowski; Sandra Hirche (Annu. Rev. Control., 2021)

KoopmanizingFlows: Diffeomorphically Learning Stable Koopman Operators. - Petar Bevanda; Max Beier; Sebastian Kerz; Armin Lederer; Stefan Sosnowski; Sandra Hirche (CoRR, 2021)

Learning the Koopman Eigendecomposition: A Diffeomorphic Approach. - Petar Bevanda; Johannes Kirmayr; Stefan Sosnowski; Sandra Hirche (ACC, 2022)

Towards Data-driven LQR with KoopmanizingFlows. - Petar Bevanda; Max Beier; Shahab Heshmati-Alamdari; Stefan Sosnowski; Sandra Hirche (CoRR, 2022)

Diffeomorphically Learning Stable Koopman Operators. - Petar Bevanda; Max Beier; Sebastian Kerz; Armin Lederer; Stefan Sosnowski; Sandra Hirche (IEEE Control. Syst. Lett., 2022)

Koopman Kernel Regression. - Petar Bevanda; Max Beier; Armin Lederer; Stefan Sosnowski; Eyke Hüllermeier; Sandra Hirche (NeurIPS, 2023)

Nonparametric Control-Koopman Operator Learning: Flexible and Scalable Models for Prediction and Control. - Petar Bevanda; Bas Driessen; Lucian-Cristian Iacob; Roland Tóth; Stefan Sosnowski; Sandra Hirche (CoRR, 2024)

Data-Driven Optimal Feedback Laws via Kernel Mean Embeddings. - Petar Bevanda; Nicolas Hoischen; Stefan Sosnowski; Sandra Hirche; Boris Houska (CoRR, 2024)

Koopman-Equivariant Gaussian Processes. - Petar Bevanda; Max Beier; Alexandre Capone; Stefan Sosnowski; Sandra Hirche; Armin Lederer (AISTATS, 2025)

Kernel-Based Optimal Control: An Infinitesimal Generator Approach. - Petar Bevanda; Nicolas Hoischen; Tobias Wittmann; Jan Brüdigam; Sandra Hirche; Boris Houska (L4DC, 2025)