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Stefano Favaro
Stefano Favaro
University of Torino and Collegio Carlo Alberto
Email verificata su unito.it - Home page
Titolo
Citata da
Citata da
Anno
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
2092013
MCMC for normalized random measure mixture models
S Favaro, YW Teh
Statistical Science 28 (3), 335-359, 2013
1402013
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
1222009
A new estimator of the discovery probability
S Favaro, A Lijoi, I Prünster
Biometrics 68 (4), 1188-1196, 2012
602012
On the stick-breaking representation of normalized inverse Gaussian priors
S Favaro, A Lijoi, I Prünster
Biometrika 99 (3), 663-674, 2012
472012
Conditional formulae for Gibbs-type exchangeable random partitions
S Favaro, A Lijoi, I Pruenster
The Annals of Applied Probability 23 (5), 1721-1754, 2013
462013
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
442017
Infinitely deep neural networks as diffusion processes
S Peluchetti, S Favaro
International Conference on Artificial Intelligence and Statistics, 1126-1136, 2020
422020
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
392011
Slice sampling σ-stable Poisson-Kingman mixture models
S Favaro, SG Walker
Journal of Computational and Graphical Statistics 22 (4), 830-847, 2013
342013
Stable behaviour of infinitely wide deep neural networks
S Peluchetti, S Favaro, S Fortini
International Conference on Artificial Intelligence and Statistics, 1137-1146, 2020
332020
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
312016
Sufficientness postulates for Gibbs-type priors and hierarchical generalizations
S Bacallado, M Battiston, S Favaro, L Trippa
Statistical Science, 487-500, 2017
282017
Rediscovery of Good–Turing estimators via Bayesian nonparametrics
S Favaro, B Nipoti, YW Teh
Biometrics 72 (1), 136-145, 2016
252016
Alpha-diversity processes and normalized inverse-Gaussian diffusions
M Ruggiero, SG Walker, S Favaro
The Annals of Applied Probability 23 (1), 386-425, 2013
252013
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
242022
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 analysis of reversible Markov chains
S Bacallado, S Favaro, L Trippa
The Annals of Statistics, 870-896, 2013
242013
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
232017
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
212017
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Articoli 1–20