Umberto Picchini
I am Associate Professor in Mathematical Statistics at the Department of Mathematical Sciences, Gothenburg University and Chalmers University of Technology. My research is mainly devoted to statistical inference for dynamical systems and stochastic processes, especially stochastic differential equations (SDEs). Applied work focuses on stochastic mathematical modelling of biomedical issues. My research topics are: Monte Carlo methods in Statistics, Bayesian inference, approximate Bayesian computation (ABC); methods for intractable likelihoods; inference for hierarchical (mixed-effects) models defined by SDEs.
Showing 12 publications
Towards data-conditional simulation for ABC inference in stochastic differential equations
Guided sequential ABC schemes for intractable Bayesian models
JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models
Sequentially Guided MCMC Proposals for Synthetic Likelihoods and Correlated Synthetic Likelihoods
Statistical modeling of diabetic neuropathy: Exploring the dynamics of nerve mortality
Scalable and flexible inference framework for stochastic dynamic single-cell models
Sequential Neural Posterior and Likelihood Approximation
Accelerating delayed-acceptance Markov chain Monte Carlo algorithms
Download publication list
You can download this list to your computer.
Filter and download publication list
As logged in user (Chalmers employee) you find more export functions in MyResearch.
You may also import these directly to Zotero or Mendeley by using a browser plugin. These are found herer:
Zotero Connector
Mendeley Web Importer
The service SwePub offers export of contents from Research in other formats, such as Harvard and Oxford in .RIS, BibTex and RefWorks format.