Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference. - Max-Heinrich Laves; Sontje Ihler; Karl-Philipp Kortmann; Tobias Ortmaier (CoRR, 2019)

Calibration of Model Uncertainty for Dropout Variational Inference. - Max-Heinrich Laves; Sontje Ihler; Karl-Philipp Kortmann; Tobias Ortmaier (CoRR, 2020)

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 (ICIT, 2021)

Autoencoder-based Representation Learning from Heterogeneous Multivariate Time Series Data of Mechatronic Systems. - Karl-Philipp Kortmann; Moritz Fehsenfeld; Mark Wielitzka (CoRR, 2021)

A Recursive Gaussian Process based Online Driving Style Analysis. - Daniel Fink; Tobias Dues; Karl-Philipp Kortmann; Pascal Blum; Christoph Schweers; Ahmed Trabelsi (ACC, 2023)

Transformer Neural Networks for Maximum Friction Coefficient Estimation of Tire-Road Contact using Onboard Vehicle Sensors. - Hendrik Schäfke; Nicolas Lampe; Karl-Philipp Kortmann (CDC, 2023)

Comparative Study of Excitation Signals for Active Fault Diagnosis of Belt Drives. - Moritz Fehsenfeld; Johannes Kühn; Karl-Philipp Kortmann (ISIE, 2023)

Active Excitations for Maximum Friction Coefficient Estimation. - Nicolas Lampe; Karl-Philipp Kortmann; Clemens Westerkamp; Hans-Georg Jacob (IV, 2023)

Friction and Road Condition Estimation using Dynamic Bayesian Networks*. - Björn Volkmann; Karl-Philipp Kortmann; Thomas Seel (SDF-MFI, 2023)

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 (IV, 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)