Karl-Philipp Kortmann

According to our database, Karl-Philipp Kortmann authored at least 10 papers between 2019 and 2024.

Collaborative distances:

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

2024

Predictive Energy Management for Recuperation Axles in Refrigerated Trailers.

Dennis Bank, Simon F. G. Ehlers, Karl-Philipp Kortmann, Zeller Tobias, Cujic Patrick, Thomas Seel

CoRR, 2024

Model-Based Maximum Friction Coefficient Estimation for Road Surfaces with Gradient or Cross-Slope.

Nicolas Lampe, Simon F. G. Ehlers, Karl-Philipp Kortmann, Clemens Westerkamp, Thomas Seel

Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

2023

Active Excitations for Maximum Friction Coefficient Estimation.

Nicolas Lampe, Karl-Philipp Kortmann, Clemens Westerkamp, Hans-Georg Jacob

Proceedings of the IEEE Intelligent Vehicles Symposium, 2023

Comparative Study of Excitation Signals for Active Fault Diagnosis of Belt Drives.

Moritz Fehsenfeld, Johannes Kühn, Karl-Philipp Kortmann

Proceedings of the 32nd IEEE International Symposium on Industrial Electronics, 2023

Transformer Neural Networks for Maximum Friction Coefficient Estimation of Tire-Road Contact using Onboard Vehicle Sensors.

Hendrik Schäfke, Nicolas Lampe, Karl-Philipp Kortmann

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

A Recursive Gaussian Process based Online Driving Style Analysis.

Daniel Fink, Tobias Dues, Karl-Philipp Kortmann, Pascal Blum, Christoph Schweers, Ahmed Trabelsi

Proceedings of the American Control Conference, 2023

2021

Autoencoder-based Representation Learning from Heterogeneous Multivariate Time Series Data of Mechatronic Systems.

Karl-Philipp Kortmann, Moritz Fehsenfeld, Mark Wielitzka

CoRR, 2021

Estimation of Stochastic Time Lags between Data Sources in Distributed Production Facilities Based on Cross-Correlated Signals.

Johannes Zumsande, Karl-Philipp Kortmann, Tobias Ortmaier, Mark Wielitzka

Proceedings of the 22nd IEEE International Conference on Industrial Technology, 2021

2020

Calibration of Model Uncertainty for Dropout Variational Inference.

Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann, Tobias Ortmaier

CoRR, 2020

2019

Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference.

Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann, Tobias Ortmaier

CoRR, 2019