1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CV2024★ 1 cited
Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning
Nils Lehmann, Jakob Gawlikowski, Adam J. Stewart +4
Uncertainty quantification (UQ) is an essential tool for applying deep neural networks (DNNs) to real world tasks, as it attaches a degree of confidence to DNN outputs. However, de…
physics.ao-ph2024★ 1 cited
Uncertainty Aware Tropical Cyclone Wind Speed Estimation from Satellite Data
Nils Lehmann, Nina Maria Gottschling, Stefan Depeweg +1
Deep neural networks (DNNs) have been successfully applied to earth observation (EO) data and opened new research avenues. Despite the theoretical and practical advances of these t…