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Grant Award View - GA64749-V1
Advances in Sequential Monte Carlo Methods for Complex Bayesian Models
GA ID:
GA64749-V1
Agency:
Australian Research Council
Approval Date:
4-Dec-2019
Variation Publish Date:
23-Jun-2020
Variation Date:
23-Jun-2020
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
12-May-2020 to 11-May-2023
Value (AUD):
$390,000.00
(GST inclusive where applicable)
Varies:
GA64749
- Advances in Sequential Monte Carlo Methods for Complex Bayesian Models
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 19/20 Discovery
Grant Program:
Discovery Projects
Grant Activity:
Advances in Sequential Monte Carlo Methods for Complex Bayesian Models
Purpose:
This project aims to develop efficient statistical algorithms for parameter estimation of complex stochastic models that currently cannot be handled. Parameter estimation is an essential component of mathematical modelling for answering scientific questions and revealing new insights. Current parameter estimation methods can be inefficient and require too much user intervention. This project will develop novel Bayesian algorithms that are optimally automated and efficient by exploiting ever-improving parallel computing devices. The new methods will allow practitioners to process realistic models, enabling new scientific discoveries in a wide range of disciplines such as biology, ecology, agriculture, hydrology and finance.
GO ID:
GO Title:
Discovery Projects for funding commencing in 2020
Internal Reference ID:
DP20 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
Queensland University of Technology
Recipient ABN:
83 791 724 622
Grant Recipient Location
Suburb:
BRISBANE CITY
Town/City:
BRISBANE CITY
Postcode:
4000
State/Territory:
QLD
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
QLD
Postcode:
4000
Country:
AUSTRALIA