Prof. François Caron
Prof. François Caron’s research interests lie in the development of statistical models and computational procedures for the analysis of structured data, with particular interest in Bayesian nonparametrics and Monte Carlo methods. His recent research focuses on building probabilistic models of network data which can capture the salient properties of real-world networks (sparsity, modularity), as well as efficient algorithms for learning the hidden structure of those networks.
Selected Publications
Caron, F., Teh, Y.W. and Murphy, T.B. (2014) ‘Bayesian nonparametric Plackett–Luce models for the analysis of preferences for college degree programmes’, The Annals of Applied Statistics, 8(2), pp. 1145–1181.
Todeschini, A., Caron, F. and Chavent, M. (2013) ‘Probabilistic low-rank matrix completion with Adaptive spectral Regularization Algorithms’, Neural Information Processing Systems.
Caron, F. (2012) ‘Bayesian nonparametric models for bipartite graphs’, Neural Information Processing Systems.
Lee, A., Caron, F., Doucet, A. and Holmes, C. (2012) ‘Bayesian Sparsity-Path-Analysis of genetic association signal using generalized t Priors’, Statistical Applications in Genetics and Molecular Biology, 11(2).
Caron, F., Doucet, A. and Gottardo, R. (2011) ‘On-line changepoint detection and parameter estimation with application to genomic data’, Statistics and Computing, 22(2), pp. 579–595.
