66 citations · 132 across the 11 of their papers we have counts for
4 papers · 1 filter
Bayesian Semi-structured Subspace Inference
Daniel Dold, David Rügamer, Beate Sick +1
Semi-structured regression models enable the joint modeling of interpretable structured and complex unstructured feature effects. The structured model part is inspired by statistic…
Single-shot Bayesian approximation for neural networks
Kai Brach, Beate Sick, Oliver Dürr
Deep neural networks (NNs) are known for their high-prediction performances. However, NNs are prone to yield unreliable predictions when encountering completely new situations with…
Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flows
Marcel Arpogaus, Marcus Voss, Beate Sick +2
The transition to a fully renewable energy grid requires better forecasting of demand at the low-voltage level to increase efficiency and ensure reliable control. However, high flu…
Single Shot MC Dropout Approximation
Kai Brach, Beate Sick, Oliver Dürr
Deep neural networks (DNNs) are known for their high prediction performance, especially in perceptual tasks such as object recognition or autonomous driving. Still, DNNs are prone…