Universal uncertainty quantification using deep learning. This project aims to develop a new and universal approach to uncertainty quantification using deep learning. This project expects to use innov

Description

Universal uncertainty quantification using deep learning. This project aims to develop a new and universal approach to uncertainty quantification using deep learning. This project expects to use innovative deep learning tools to develop the first simultaneously tractable and expressive models that can be used directly to quantify uncertainty, a significant unsolved problem. Expected outcomes of this project include a general framework for directly quantifying uncertainty, surpassing current methods which are unable to use big data or are indirect, slow, inexact or inexpressive. This should provide significant benefits for trusted uncertainty quantification using deep learning, with demonstrated downstream applications in manufacturing and coastal bathymetry.. Scheme: Discovery Early Career Researcher Award. Field: 4611 - Machine Learning. Lead: Dr Russell Tsuchida