Neural Roll Angle Estimation in a Model Predictive Control System. - Sebastian Blume; Philipp Maximilian Sieberg; Niko Maas; Dieter Schramm (ITSC, 2019)

Hybrid State Estimation Combining Artificial Neural Network and Physical Model. - Philipp Maximilian Sieberg; Sebastian Blume; Nele Harnack; Niko Maas; Dieter Schramm (ITSC, 2019)

Development and Validation of Active Roll Control based on Actor-critic Neural Network Reinforcement Learning. - Matthias Bahr; Sebastian Reicherts; Philipp Maximilian Sieberg; Luca Morss; Dieter Schramm (SIMULTECH, 2019)

Representation of an Integrated Non-Linear Model-Based Predictive Vehicle Dynamics Control System by a Co-Active Neuro-Fuzzy Inference System. - Philipp Maximilian Sieberg; Christian Hürten; Dieter Schramm (IV, 2020)

Template for Preparation of Papers for IEEE Sponsored Conferences & Symposia. - Maximilian Jarofka; Philipp Maximilian Sieberg; Christian Hürten; Tim Benedens; Ricarda Peters; Frédéric Etienne Kracht; Dieter Schramm (ITSC, 2022)

Generating a Multi-fidelity Simulation Model Estimating the Models' Applicability with Machine Learning Algorithms. - Christian Hürten; Philipp Maximilian Sieberg; Dieter Schramm (SIMULTECH, 2022)

Ensuring the Reliability of Virtual Sensors Based on Artificial Intelligence within Vehicle Dynamics Control Systems. - Philipp Maximilian Sieberg; Dieter Schramm (Sensors, 2022)

Hybrid State Estimation-A Contribution Towards Reliability Enhancement of Artificial Neural Network Estimators. - Philipp Maximilian Sieberg; Sebastian Blume; Sebastian Reicherts; Niko Maas; Dieter Schramm (IEEE Trans. Intell. Transp. Syst., 2022)

Estimation of Vehicle States Using a Cascaded Hybrid Estimation Method. - Marvin Glomsda; Hendrik Tino Prümer; Philipp Maximilian Sieberg (SIMULTECH, 2025)