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Artificial Intelligence for Decision Making: Machine learned models from simulation data

Project Member(s): Bishop, A.

Funding or Partner Organisation: NSW Department of Industry (NSW Defence Innovation Network)
NSW Department of Industry (NSW Defence Innovation Network)

Start year: 2020

Summary: The idea for this project is to evaluate how well data generated by the simulation of a model can be analysed using machine learning techniques to create a meta-model of the simulation itself. This meta-model is especially desirable if it is more efficient than the simulation in terms of time and/or computational resources.


Bishop, AN & Del Moral, P 2023, 'Robust Kalman and Bayesian Set-Valued Filtering and Model Validation for Linear Stochastic Systems', SIAM/ASA Journal on Uncertainty Quantification, vol. 11, no. 2, pp. 389-425.
View/Download from: Publisher's site

Bishop, AN & Bonilla, EV 1970, 'Recurrent Neural Networks and Universal Approximation of Bayesian Filters', Proceedings of Machine Learning Research, pp. 6956-6967.

FOR Codes: Numerical and computational mathematics, Statistics, Emerging Defence Technologies