11 citations · 12 across the 2 of their papers we have counts for
3 papers
Autoencoder-based Representation Learning from Heterogeneous Multivariate Time Series Data of Mechatronic Systems
Karl-Philipp Kortmann, Moritz Fehsenfeld, Mark Wielitzka
Sensor and control data of modern mechatronic systems are often available as heterogeneous time series with different sampling rates and value ranges. Suitable classification and r…
Calibration of Model Uncertainty for Dropout Variational Inference
Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann +1
The model uncertainty obtained by variational Bayesian inference with Monte Carlo dropout is prone to miscalibration. In this paper, different logit scaling methods are extended to…
Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference
Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann +1
Model uncertainty obtained by variational Bayesian inference with Monte Carlo dropout is prone to miscalibration. The uncertainty does not represent the model error well. In this p…