Website
http://dataportal.arc.gov.au/NCGP/API/grants/DP190102181
Funding Status
Active
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Funded Activity Summary
Quantification, optimisation, and application of deep uncertainty. This project aims to develop a framework for deep uncertainty quantification. There is currently a fundamental gap between deep learning research and the methods required to quantify and manage uncertainties. The research will propose a novel distribution-free methodology to generate deep predictive uncertainty estimates to avoid the assumptions of existing methods. The quality of estimates will be enhanced by applying an interval-based adversarial training step. The project is expected to help data-driven Australian organisations and industries to better quantify and manage forecasting uncertainties. This project will provide them with significant cost savings through better decision making and more robust planning.Funded Activity Details
Start Date: 03-2019
End Date: 12-2024
Funding Scheme: Discovery Projects
Funding Amount: $431,709.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Power and Energy Systems Engineering (excl. Renewable Power) | Simulation and Modelling | Neural, Evolutionary and Fuzzy Computation | Artificial Intelligence and Image Processing
ANZSRC Socio-Economic Objective (SEO)
Energy Services and Utilities | Renewable Energy not elsewhere classified | Wind Energy |
