I am a Research Fellow in the Warwick Machine Learning Group working with Adam Johansen and Theo Damoulas. My research interests lie in Monte Carlo, computational statistics, optimization, and statistical machine learning. My current work focuses on extensions of sequential Monte Carlo for models lacking time-series structure (see here), exploiting conditional independeces to improve the performance of Monte Carlo estimators on high-dimensional targets (see here), and the interplay between inference procedures and optimization algorithms on measure spaces. In the past, I have worked on Markov processes and numerical techniques for the analysis thereof. Below are a few recent preprints and 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, F. R. Crucinio, A. M. Johansen. The divide-and-conquer sequential Monte Carlo algorithm: theoretical properties and limit theorems, 2021 [arXiv].
- J. Kuntz, F. R. Crucinio, A. M. Johansen. Product-form estimators: exploiting independence to scale up Monte Carlo, Statistics and Computing, 32:12, 2022 [journal].
- 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. Approximations of Countably Infinite Linear Programs over Bounded Measure Spaces, SIAM Journal on Optimization, 31(1):604-625, 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].