1 citations · 2 across the 5 of their papers we have counts for
5 papers
Remember to correct the bias when using deep learning for regression!
Christian Igel, Stefan Oehmcke
When training deep learning models for least-squares regression, we cannot expect that the training error residuals of the final model, selected after a fixed training time or base…
Attentional Feature Fusion
Yimian Dai, Fabian Gieseke, Stefan Oehmcke +2
Feature fusion, the combination of features from different layers or branches, is an omnipresent part of modern network architectures. It is often implemented via simple operations…
Attention as Activation
Yimian Dai, Stefan Oehmcke, Fabian Gieseke +2
Activation functions and attention mechanisms are typically treated as having different purposes and have evolved differently. However, both concepts can be formulated as a non-lin…
Magnitude and Uncertainty Pruning Criterion for Neural Networks
Vinnie Ko, Stefan Oehmcke, Fabian Gieseke
Neural networks have achieved dramatic improvements in recent years and depict the state-of-the-art methods for many real-world tasks nowadays. One drawback is, however, that many…
Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data
Stefan Oehmcke, Christoffer Thrysøe, Andreas Borgstad +3
Massive amounts of satellite data have been gathered over time, holding the potential to unveil a spatiotemporal chronicle of the surface of Earth. These data allow scientists to i…