142 citations · 600 across the 47 of their papers we have counts for
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Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC
Maurizio Filippone
Kernel methods have revolutionized the fields of pattern recognition and machine learning. Their success, however, critically depends on the choice of kernel parameters. Using Gaus…
Pseudo-Marginal Bayesian Inference for Gaussian Processes
Maurizio Filippone, Mark Girolami
The main challenges that arise when adopting Gaussian Process priors in probabilistic modeling are how to carry out exact Bayesian inference and how to account for uncertainty on m…
Bayesian nonparametric disclosure risk estimation via mixed effects log-linear models
Cinzia Carota, Maurizio Filippone, Roberto Leombruni +1
Statistical agencies and other institutions collect data under the promise to protect the confidentiality of respondents. When releasing microdata samples, the risk that records ca…
Probabilistic prediction of neurological disorders with a statistical assessment of neuroimaging data modalities
M. Filippone, A. F. Marquand, C. R. V. Blain +3
For many neurological disorders, prediction of disease state is an important clinical aim. Neuroimaging provides detailed information about brain structure and function from which…