Stefano Favaro

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Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindAdresse e-mail validée de stats.ox.ac.uk
Stefano PeluchettiResearch Scientist, Sakana AIAdresse e-mail validée de sakana.ai
lorenzo trippaHarvard and Dana FarberAdresse e-mail validée de jimmy.harvard.edu
Emanuele Doleraricercatore in probabilità e statistica, Università di PaviaAdresse e-mail validée de unipv.it
Sergio BacalladoAssociate Professor of Statistics, University of CambridgeAdresse e-mail validée de cam.ac.uk
Bernardo NipotiUniversity of Milano Bicocca, ItalyAdresse e-mail validée de unimib.it
Ramsés H MenaIIMAS-UNAMAdresse e-mail validée de sigma.iimas.unam.mx
Lorenzo MasoeroApplied Scientist, AmazonAdresse e-mail validée de mit.edu
Maria De IorioProfessor of Biostatistics, National University of SingaporeAdresse e-mail validée de nus.edu.sg
Matteo SesiaUniversity of Southern CaliforniaAdresse e-mail validée de usc.edu
Zacharie NauletUniversité Paris-SaclayAdresse e-mail validée de universite-paris-saclay.fr
Boyu RenMcLean HospitalAdresse e-mail validée de partners.org
Maria LomeliMeta FAIRAdresse e-mail validée de meta.com
Julyan ArbelInria - Univ. Grenoble AlpesAdresse e-mail validée de inria.fr
Mario BerahaDepartment of Mathematics, Politecnico di MilanoAdresse e-mail validée de polimi.it
Tamara BroderickAssociate Professor of EECS, Massachusetts Institute of TechnologyAdresse e-mail validée de mit.edu
Fadhel AyedDepartment of Statistics, University of OxfordAdresse e-mail validée de some.ox.ac.uk
Daniele BracalePhD StatisticsAdresse e-mail validée de umich.edu
Susan P HolmesProfessor of Statistics, Stanford UniversityAdresse e-mail validée de stat.stanford.edu
Alessandra GuglielmiProfessor of Statistics, Department of Mathematics, Politecnico di MilanoAdresse e-mail validée de polimi.it

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Stefano Favaro

University of Torino and Collegio Carlo Alberto

Adresse e-mail validée de unito.it - Page d'accueil

Bayesian nonparametric statistics


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	223	2013
MCMC for normalized random measure mixture models S Favaro, YW Teh Statistical Science 28 (3), 335-359, 2013	141	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	131	2009
A new estimator of the discovery probability S Favaro, A Lijoi, I Prünster Biometrics 68 (4), 1188-1196, 2012	62	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	50	2013
On the stick-breaking representation of normalized inverse Gaussian priors S Favaro, A Lijoi, I Prünster Biometrika 99 (3), 663-674, 2012	47	2012
Infinitely deep neural networks as diffusion processes S Peluchetti, S Favaro International Conference on Artificial Intelligence and Statistics, 1126-1136, 2020	45	2020
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	45	2017
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	41	2011
Stable behaviour of infinitely wide deep neural networks S Peluchetti, S Favaro, S Fortini International Conference on Artificial Intelligence and Statistics, 1137-1146, 2020	35	2020
Sufficientness postulates for Gibbs-type priors and hierarchical generalizations S Bacallado, M Battiston, S Favaro, L Trippa Statistical Science, 487-500, 2017	31	2017
Slice sampling σ-stable Poisson-Kingman mixture models S Favaro, SG Walker Journal of Computational and Graphical Statistics 22 (4), 830-847, 2013	31	2013
More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics L Masoero, F Camerlenghi, S Favaro, T Broderick Biometrika 109 (1), 17-32, 2022	29	2022
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	29	2016
Rediscovery of Good–Turing estimators via Bayesian nonparametrics S Favaro, B Nipoti, YW Teh Biometrics 72 (1), 136-145, 2016	27	2016
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	25	2017
Bayesian nonparametric analysis of reversible Markov chains S Bacallado, S Favaro, L Trippa The Annals of Statistics, 870-896, 2013	25	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	25	2013
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	24*	2020
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	22	2017

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