Massimiliano Tamborrino
Associate Professor (Reader)
Department of Statistics
Office: MSB 1.23
Email: massimiliano.tamborrino@warwick.ac.uk
Webpage: https://warwick.ac.uk/tamborrino/
Research interests:
- Mathematical modelling in neuroscience and biology;
- Stochastic numerics for dynamical systems;
- Inference for neuronal models and beyond;
- Probabilistic parallel-in-time numerical schemes for complex ODEs/PDEs.
Selected publications:
- S. Ditlevsen, M. Tamborrino, I. Tubikanec. Network inference in a stochastic multi-population neural mass model via approximate Bayesian computation, 2023. Preprint at Arxiv https://arxiv.org/abs/2306.15787
- U. Picchini, M. Tamborrino. Guided sequential ABC schemes for intractable Bayesian modelsLink opens in a new window, Bayesian Analysis Advance Publication 1-32, 2024. DOI: 10.1214/24-BA1451
- E Buckwar, A Samson, M Tamborrino, I Tubikanec. A splitting method for SDEs with locally Lipschitz drift: Illustration on the FitzHugh-Nagumo model . Link opens in a new windowApplied Numerical Mathematics 179, 191-220, 2022.
- K Pentland, M Tamborrino, TJ Sullivan, J Buchanan, LC Appel. GParareal: a time-parallel ODE solver using Gaussian process emulationLink opens in a new window. Statistics and Computing 33 (1), 23, 2023
- E Buckwar, M Tamborrino, I Tubikanec. Spectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEsLink opens in a new window, 30, 627–648, 2020