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Grant Award View - GA215143-V1
A dynamical systems theory approach to machine learning
GA ID:
GA215143-V1
Agency:
Australian Research Council
Approval Date:
19-Jan-2022
Variation Publish Date:
21-Apr-2022
Variation Date:
1-Jun-2022
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jun-2022 to 31-May-2025
Value (AUD):
$356,000.00
(GST inclusive where applicable)
Varies:
GA215143
- A dynamical systems theory approach to machine learning
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 21/22 Discovery
Grant Program:
Discovery Projects
Grant Activity:
A dynamical systems theory approach to machine learning
Purpose:
Forecasting the future state of a high-dimensional complex multi-scale system is a challenge we face in areas ranging from climate science to epidemiology. Even when basic physical mechanisms have been identified, the actual evolution equations are often unknown. This project will develop a computationally cheap machine learning framework for forecasting. The proposed mathematical framework provides a forecast together with a quantification of its uncertainty. We will develop sophisticated mathematical theory underpinning the novel methodology, as well as applying it to the perennial problem of subgrid-scale parametrisation of tropical convection, a missing key element in current climate models.
GO ID:
GO Title:
Discovery Projects for funding commencing in 2022
Internal Reference ID:
DP22 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
The University of Sydney
Recipient ABN:
15 211 513 464
Grant Recipient Location
Suburb:
FOREST LODGE
Town/City:
FOREST LODGE
Postcode:
2037
State/Territory:
NSW
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
NSW
Postcode:
2037
Country:
AUSTRALIA