Mattias VillaniProfessor
Om mig
Jag är professor i statistik vid Stockholms universitet och Linköpings universitet.
I min forskning utvecklar jag beräkningseffektiva bayesianska metoder för inferens, prediktion och beslutsfattande med flexibla sannolikhetsmodeller.
Mina nuvarande tillämpingsområden är maskininlärning, transport, neuroimaging och ekonomi.
Jag undervisar för nuvarande masterkurserna Bayesiansk inlärning, 7.5 hp och Maskininlärning, 7.5 hp. Varannat år ger jag också doktorandkursen Advanced Bayesian Learning, 8 hp.
Utvalda publikationer
- The block-Poisson estimator for optimally tuned exact subsampling MCMC, Journal of Computational and Graphical Statistics, 2021 (with Matias Quiroz, Minh Ngoc Tran, Robert Kohn, and Khue-Dung Dang).
- Hamiltonian Monte Carlo with Energy Conserving Subsampling, Journal of Machine Learning Research, 2019 (with Khue-Dung Dang, Matias Quiroz, Robert Kohn and Minh Ngoc Tran)
- Speeding Up MCMC by Efficient Data Subsampling, Journal of the American Statistical Association, 2018 (with Matias Quiroz, Robert Kohn and Minh Ngoc Tran)
- Sparse Partially Collapsed MCMC for Parallel Inference in Topic Models, Journal of Computational and Graphical Statistics, 2018 (with Måns Magnusson, Leif Jonsson and David Broman)
- Fast Bayesian Whole-Brain fMRI Analysis with Spatial 3D Priors, NeuroImage, 2017 (with Per Sidén, Anders Eklund and David Bolin).
- Generalized Smooth Finite Mixtures, Journal of Econometrics, 2012 (with Robert Kohn and David Nott).
- Efficient Bayesian Multivariate Surface Regression, Scandinavian Journal of Statistics, 2013 (with Feng Li).
- Steady State Priors for Vector Autoregressions, Journal of Applied Econometrics, 2009.
- Bayesian Estimation of an Open Economy DSGE Model with Incomplete Pass-Through, Journal of International Economics, 2007 (with Malin Adolfson, Stefan Laséen and Jesper Lindé).
- Bayesian Point Estimation of the Cointegration Space, Journal of Econometrics, 2006.
- Bayesian Reference Analysis of Cointegration, Econometric Theory, 2005.
