Bayesian calibration of stochastic agent based model via random forest

C Robertson, C Safta, N Collier, J Ozik… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Agent-based models (ABM) provide an excellent framework for modeling outbreaks and
interventions in epidemiology by explicitly accounting for diverse individual interactions and …

Uncertainty Quantification for Agent Based Models: A Tutorial

L Kimpton, P Challenor, J Salter - arxiv preprint arxiv:2409.16776, 2024‏ - arxiv.org
We explore the application of uncertainty quantification methods to agent-based models
(ABMs) using a simple sheep and wolf predator-prey model. This work serves as a tutorial …

Towards Improved Uncertainty Quantification of Stochastic Epidemic Models Using Sequential Monte Carlo

A Fadikar, A Stevens, N Collier, KB Toh… - 2024 IEEE …, 2024‏ - ieeexplore.ieee.org
Sequential Monte Carlo (SMC) algorithms represent a suite of robust computational
methodologies utilized for state estimation and parameter inference within dynamical …

Gearing Gaussian process modeling and sequential design towards stochastic simulators

M Binois, A Fadikar, A Stevens - arxiv preprint arxiv:2412.07306, 2024‏ - arxiv.org
This chapter presents specific aspects of Gaussian process modeling in the presence of
complex noise. Starting from the standard homoscedastic model, various generalizations …

Distributed Model Exploration with EMEWS

N Collier, JM Wozniak, A Fadikar… - 2024 Winter …, 2024‏ - ieeexplore.ieee.org
As high-performance computing resources have become increasingly available, new modes
of applying and experimenting with simulation and other computational tools have become …