H. Røstum

Deep Gaussian Processes for Probabilistic Prediction of UAV Propeller Aerodynamics

This work evaluates Deep Gaussian Processes (DGPs) as probabilistic surrogate models for predicting thrust and torque of small Unmanned Aerial Vehicle (UAV) propellers. Unlike deterministic neural-network models, DGPs provide predictive uncertainty estimates in addition to mean predictions. Compared with standard Gauss...