Stefano Favaro

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Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindEmail yang diverifikasi di stats.ox.ac.uk
Stefano PeluchettiResearch Scientist, Sakana AIEmail yang diverifikasi di sakana.ai
lorenzo trippaHarvard and Dana FarberEmail yang diverifikasi di jimmy.harvard.edu
Emanuele Doleraricercatore in probabilità e statistica, Università di PaviaEmail yang diverifikasi di unipv.it
Sergio BacalladoAssociate Professor of Statistics, University of CambridgeEmail yang diverifikasi di cam.ac.uk
Bernardo NipotiUniversity of Milano Bicocca, ItalyEmail yang diverifikasi di unimib.it
Ramsés H MenaIIMAS-UNAMEmail yang diverifikasi di sigma.iimas.unam.mx
Lorenzo MasoeroApplied Scientist, AmazonEmail yang diverifikasi di mit.edu
Maria De IorioProfessor of Biostatistics, National University of SingaporeEmail yang diverifikasi di nus.edu.sg
Matteo SesiaUniversity of Southern CaliforniaEmail yang diverifikasi di usc.edu
Zacharie NauletUniversité Paris-SaclayEmail yang diverifikasi di universite-paris-saclay.fr
Boyu RenMcLean HospitalEmail yang diverifikasi di partners.org
Maria LomeliMeta, FAIREmail yang diverifikasi di meta.com
Julyan ArbelInria - Univ. Grenoble AlpesEmail yang diverifikasi di inria.fr
Mario BerahaDepartment of Mathematics, Politecnico di MilanoEmail yang diverifikasi di polimi.it
Tamara BroderickAssociate Professor of EECS, Massachusetts Institute of TechnologyEmail yang diverifikasi di mit.edu
Fadhel AyedDepartment of Statistics, University of OxfordEmail yang diverifikasi di some.ox.ac.uk
Daniele BracalePhD StatisticsEmail yang diverifikasi di umich.edu
Susan P HolmesProfessor of Statistics, Stanford UniversityEmail yang diverifikasi di stat.stanford.edu
Alessandra GuglielmiProfessor of Statistics, Department of Mathematics, Politecnico di MilanoEmail yang diverifikasi di polimi.it

Ikuti

Stefano Favaro

University of Torino and Collegio Carlo Alberto

Email yang diverifikasi di unito.it - Beranda

Bayesian nonparametric statistics


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
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	213	2013
MCMC for normalized random measure mixture models S Favaro, YW Teh Statistical Science 28 (3), 335-359, 2013	139	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	130	2009
A new estimator of the discovery probability S Favaro, A Lijoi, I Prünster Biometrics 68 (4), 1188-1196, 2012	61	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	49	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	44	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
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
Sufficientness postulates for Gibbs-type priors and hierarchical generalizations S Bacallado, M Battiston, S Favaro, L Trippa Statistical Science, 487-500, 2017	29	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	29	2016
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	27	2022
Rediscovery of Good–Turing estimators via Bayesian nonparametrics S Favaro, B Nipoti, YW Teh Biometrics 72 (1), 136-145, 2016	27	2016
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
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	24	2017
Bayesian nonparametric analysis of reversible Markov chains S Bacallado, S Favaro, L Trippa The Annals of Statistics, 870-896, 2013	24	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	23*	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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