I am a Research Fellow working with Adam Johansen and Theo Damoulas on the Robust, Scalable Sequential Monte Carlo with Application To Urban Air Quality project. My research interests mainly lie in Monte Carlo methods, convex optimisation, Markov processes, and numerical techniques for the study thereof. My current work focuses on developing sequential Monte Carlo methods. Below are a few recent publications, please see here for the complete list. I have also been writing a book on Markov chains, see here for the latest draft.
- J. Kuntz, P. Thomas, G.-B. Stan, M. Barahona. Stationary distributions of continuous-time Markov chains: a review of theory and truncation-based approximations, SIAM Review, 63(1):3-64, 2021 [journal|arxiv].
- J. Kuntz, P. Thomas, G.-B. Stan, M. Barahona. Bounding the stationary distributions of the chemical master equation via mathematical programming. The Journal of Chemical Physics 151(3):034109, 2019 [journal|arxiv].
- J. Kuntz, P. Thomas, G.-B. Stan, M. Barahona. The exit time finite state projection scheme: bounding exit distributions and occupation measures of continuous-time Markov chains. SIAM Journal on Scientific Computing 41(2):A748-A769, 2019 [journal|arxiv].
- J. Kuntz, M. Ottobre, A. M. Stuart. Diffusion limit for the Random Walk Metropolis algorithm out of stationarity. Annales de l'Institut Henri Poincaré, Probabilités et Statistiques 55(3):1599-1648, 2019 [journal|arxiv].
- J. Kuntz, M. Ottobre, A. M. Stuart. Non-stationary phase of the MALA algorithm. Stochastics and Partial Differential Equations: Analysis and Computations 6(3):446-499, 2018 [journal].
- J. Kuntz, M. Ottobre, G.-B. Stan, M. Barahona. Bounding stationary averages of polynomial diffusions via semidefinite programming. SIAM Journal on Scientific Computing 38(6):A3891-A3920, 2016 [journal].