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Umberto Picchini

Senior lecturer

Umberto Picchini
Senior lecturer
picchini@chalmers.se
+46 31-772 6414

Room number: H3030
Postal Address: Matematiska vetenskaper, Chalmers tekniska högskola och Göteborgs universitet, 412 96 Göteborg
Visiting Address: Chalmers Tvärgata 3 , 412 96 Göteborg


Applied Mathematics and Statistics at Department of Mathematical Sciences (More Information)
412 96 Göteborg
Visiting Address: Chalmers Tvärgata 3 , 412 96 Göteborg

About Umberto Picchini

I am interested in statistical inference for stochastic modelling, and especially Bayesian computational methods. For example, I am interested in MCMC, sequential Monte Carlo (particle filters) and especially “likelihood-free” methods, such as approximate Bayesian computation (ABC). I have special interest in stochastic modelling (e.g. stochastic differential equations) and applications in biomedicine.

See also http://www.chalmers.se/en/Staff/Pages/picchini.aspx

Latest publications

Accelerating delayed-acceptance Markov chain Monte Carlo algorithms
Samuel Wiqvist, Umberto Picchini, Julie Lyng Forman, Kresten Lindorff-Larsen, Wouter Boomsma
Working paper 2019
Working paper

Partially Exchangeable Networks and architectures for learning summary statistics in Approximate Bayesian Computation
Samuel Wiqvist, Pierre-Alexandre Mattei, Jes Frellsen, Umberto Picchini
Proceedings of the 36th International Conference on Machine Learning, PMLR, Conference paper 2019
Conference paper

Bayesian inference for stochastic differential equation mixed effects models of a tumor xenography study
Umberto Picchini, Julie Lyng Forman
Journal of the Royal Statistic Society, Series C: Applied Statistics, Journal article 2019
Journal article

Showing 1 - 3 of 3

2019

Accelerating delayed-acceptance Markov chain Monte Carlo algorithms
Samuel Wiqvist, Umberto Picchini, Julie Lyng Forman, Kresten Lindorff-Larsen, Wouter Boomsma
Working paper 2019
Working paper

Partially Exchangeable Networks and architectures for learning summary statistics in Approximate Bayesian Computation
Samuel Wiqvist, Pierre-Alexandre Mattei, Jes Frellsen, Umberto Picchini
Proceedings of the 36th International Conference on Machine Learning, PMLR, Conference paper 2019
Conference paper

Bayesian inference for stochastic differential equation mixed effects models of a tumor xenography study
Umberto Picchini, Julie Lyng Forman
Journal of the Royal Statistic Society, Series C: Applied Statistics, Journal article 2019
Journal article

Showing 1 - 3 of 3

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