Stefano Favaro

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Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
lorenzo trippaHarvard and Dana FarberVerified email at jimmy.harvard.edu
Bernardo NipotiUniversity of Milano Bicocca, ItalyVerified email at unimib.it
Ramsés H MenaIIMAS-UNAMVerified email at sigma.iimas.unam.mx
Emanuele Doleraricercatore in probabilità e statistica, Università di PaviaVerified email at unipv.it
Maria De IorioProfessor of Biostatistics, National University of Singapore & University College LondonVerified email at nus.edu.sg
Boyu RenMcLean HospitalVerified email at partners.org
Julyan ArbelInriaVerified email at inria.fr
Maria LomeliMeta AI, FAIRVerified email at fb.com
Lorenzo MasoeroApplied Research Scientist, AmazonVerified email at mit.edu
Fadhel AyedDepartment of Statistics, University of OxfordVerified email at some.ox.ac.uk
Tamara BroderickAssociate Professor of EECS, Massachusetts Institute of TechnologyVerified email at mit.edu
Zacharie NauletUniversité Paris-SaclayVerified email at universite-paris-saclay.fr
Matteo SesiaUniversity of Southern CaliforniaVerified email at usc.edu
Susan P HolmesProfessor of Statistics, Stanford UniversityVerified email at stat.stanford.edu
Daniele BracalePhD StatisticsVerified email at umich.edu
Tommi VatanenAssociate Professor, University of HelsinkiVerified email at helsinki.fi
Curtis HuttenhowerDepartment of Biostatistics, Harvard School of Public HealthVerified email at hsph.harvard.edu
Alessandra GuglielmiProfessor of Statistics, Department of Mathematics, Politecnico di MilanoVerified email at polimi.it
Lloyd T. ElliottSimon Fraser UniversityVerified email at sfu.ca

Stefano Favaro

University of Torino and Collegio Carlo Alberto

Verified email at unito.it - Homepage

Bayesian nonparametric statistics


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Are Gibbs-type priors the most natural generalization of the Dirichlet process? P De Blasi, S Favaro, A Lijoi, RH Mena, I Prünster, M Ruggiero IEEE transactions on pattern analysis and machine intelligence 37 (2), 212-229, 2013	165	2013
MCMC for normalized random measure mixture models S Favaro, YW Teh Statistical Science 28 (3), 335-359, 2013	131	2013
Bayesian non-parametric inference for species variety with a two-parameter Poisson–Dirichlet process prior S Favaro, A Lijoi, RH Mena, I Prünster Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2009	113	2009
A new estimator of the discovery probability S Favaro, A Lijoi, I Prünster Biometrics 68 (4), 1188-1196, 2012	55	2012
Conditional formulae for Gibbs-type exchangeable random partitions S Favaro, A Lijoi, I Pruenster The Annals of Applied Probability 23 (5), 1721-1754, 2013	45	2013
Bayesian nonparametric ordination for the analysis of microbial communities B Ren, S Bacallado, S Favaro, S Holmes, L Trippa Journal of the American Statistical Association 112 (520), 1430-1442, 2017	42	2017
On the stick-breaking representation of normalized inverse Gaussian priors S Favaro, A Lijoi, I Prünster Biometrika 99 (3), 663-674, 2012	41	2012
On a class of distributions on the simplex S Favaro, G Hadjicharalambous, I Prünster Journal of Statistical Planning and Inference 141 (9), 2987-3004, 2011	38	2011
Slice sampling σ-stable Poisson-Kingman mixture models S Favaro, SG Walker Journal of Computational and Graphical Statistics 22 (4), 830-847, 2013	30	2013
Alpha-diversity processes and normalized inverse-Gaussian diffusions M Ruggiero, SG Walker, S Favaro The Annals of Applied Probability 23 (1), 386-425, 2013	26	2013
Stable behaviour of infinitely wide deep neural networks S Peluchetti, S Favaro, S Fortini International Conference on Artificial Intelligence and Statistics, 1137-1146, 2020	25	2020
Infinitely deep neural networks as diffusion processes S Peluchetti, S Favaro International Conference on Artificial Intelligence and Statistics, 1126-1136, 2020	25	2020
Sufficientness postulates for Gibbs-type priors and hierarchical generalizations S Bacallado, M Battiston, S Favaro, L Trippa Statistical Science, 487-500, 2017	24	2017
On the stick-breaking representation for homogeneous NRMIs S Favaro, A Lijoi, C Nava, B Nipoti, I Pruenster, YW Teh Bayesian Analysis 11 (3), 697-724, 2016	23	2016
Bayesian nonparametric analysis of reversible Markov chains S Bacallado, S Favaro, L Trippa The Annals of Statistics, 870-896, 2013	23	2013
Rediscovery of Good–Turing estimators via Bayesian nonparametrics S Favaro, B Nipoti, YW Teh Biometrics 72 (1), 136-145, 2016	22	2016
Bayesian mixed effects models for zero-inflated compositions in microbiome data analysis B Ren, S Bacallado, S Favaro, T Vatanen, C Huttenhower, L Trippa The Annals of Applied Statistics 14 (1), 494-517, 2020	21*	2020
A marginal sampler for σ-stable Poisson–Kingman mixture models M Lomelí, S Favaro, YW Teh Journal of Computational and Graphical Statistics 26 (1), 44-53, 2017	21	2017
On the distribution of sums of independent exponential random variables via Wilks’ integral representation S Favaro, SG Walker Acta applicandae mathematicae 109, 1035-1042, 2010	21	2010
Bayesian nonparametric inference for discovery probabilities: Credible intervals and large sample asymptiotics J Arbel, S Favaro, B Nipoti, YW Teh Statistica Sinica, 839-858, 2017	19	2017

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