Stefano Favaro
Professor of Statistics, Università
di Torino
Departimento di Scienze EconomicoSociali e MatematicoStatistiche
Università di Torino
Corso Unione Sovietica 218/bis
10134 Torino, Italy
Telephone: +39 011 6705724
Email: stefano(.)favaro(at)unito(.)it
Cv [PDF]
Research interests: nonparametric Bayes and empirical Bayes methods,
statistical machine learning, data confidentiality and fairness,
learningaugmented recovery algorithms, mathematics of deep learning
My research is currently supported by a European Reseach Council (ERC)
Consolidator grant (2019  2024)
Papers:
1. Main
publications
 Doubly infinite neural networks: a
diffusion process approach, with S. Peluchetti
 Journal
of Machine Learning Research,
2021, vol. 22, pp. 148
 [DOI]
[PDF]
 More for less: predicting and
maximizing genetic variant discovery via Bayesian nonparametrics, with
T. Broderick, F. Camerlenghi and L. Masoero
 Biometrika,
to appear
 [DOI]
[PDF]
 Bayesian nonparametric disclosure risk assessment, with F. Panero and T. Rigon
 Electronic Journal of Statistics,
to appear
 [DOI]
[PDF]
 Optimal disclosure risk assessment,
with F. Camerlenghi, Z. Naulet and F. Panero
 Annals
of Statistics, 2021,
vol. 49, pp. 723744
 [DOI]
[PDF]
 Largewidth functional asymptotics for
deep Gaussian neural networks, with D. Bracale, S. Fortini and S.
Peluchetti
 International
Conference on Learning Representations, 2021
 [ICLR]
 A Bayesian nonparametric approach to
countmin sketch under powerlaw data streams, with E. Dolera and S.
Peluchetti
 International
Conference on Artificial Intelligence and Statistics,
2021
 [AISTATS]
 Consistent and rate optimal estimation
of the missing mass, with F. Ayed, M. Battiston and F. Camerlenghi
 Annales
de l'Institut Henri Poincaré  Probabilités et Statistiques,
2021, vol. 57, pp. 14761494
 [DOI]
[PDF]
 Perfect sampling for posterior
hierarchical PitmanYor processes, with S. Bacallado and L. Trippa
 Bayesian
Analysis, to appear
 [DOI]
[PDF]
 Consistent estimation of small masses
in feature sampling, with F. Ayed, M. Battiston and F. Camerlenghi
 Journal
of Machine Learning Research,
2021, vol. 22, pp. 128
 [DOI]
[PDF]
 Stable behaviour of infinitely wide
deep neural networks, with S. Fortini and S. Peluchetti
 International
Conference on Artificial Intelligence and Statistics, 2020
 [AISTATS]
 Infinitely deep neural networks as
diffusion processes, with S. Peluchetti
 International
Conference on Artificial Intelligence and Statistics, 2020
 [AISTATS]
 Nonparametric Bayesian multiarmed
bandits for single cell experiment design, with F. Camerlenghi, B.
Dimitrascu, B. Engelhardt and F. Ferrari
 Annals
of Applied Statistics,
2020, vol. 14, pp. 20032019
 [DOI]
[PDF]
 A GoodTuring estimator for feature
allocation models, with F. Ayed, M. Battiston and F. Camerlenghi
 Electronic
Journal of Statistics, 2019, vol. 13, pp. 37753804
 [DOI] [PDF]
 Rates of convergence in de Finetti's
representation theorem, and Hausdorff moment problem, with E. Dolera
 Bernoulli,
2020, vol. 26, pp. 12941322
 [DOI]
[PDF]
 A BerryEsseen theorem for Pitman's
alphadiversity, with E. Dolera
 Annals
of Applied Probability,
2020, vol. 30, pp. 847869
 [DOI]
[PDF]
 Approximating predictive probabilities
of Gibbstype priors, with J. Arbel
 Sankhya
Series A, 2021, vol. 83, pp. 496519
 [DOI]
 Bayesian mixed effects models for
zeroinflated compositions in microbiome data analysis, with S.
Bacallado, C. Huttenhower, B. Ren and L. Trippa
 Annals
of Applied Statistics, 2020, vol. 14, pp. 494517
 [DOI]
[PDF]
 Multiarmed bandits for species
discovery: a Bayesian nonparametric approach, with M. Battiston and Y.W.
Teh
 Journal
of the American Statistical Association, 2018, vol. 113, pp.
455466
 [DOI]
 Dependent generalized Dirichlet priors
for the analysis of acute lymphoblastic leukaemia, with W. Barcella, M.
De Iorio and G. Rosner
 Biostatistics,
2018, vol. 19, pp. 342358
 [DOI]
 Bayesian nonparametric analysis of
Kingman's coalescent, with S. Feng and P. Jenkins
 Annales
de l'Institut Henri Poincaré  Probabilités et Statistiques,
2019, vol. 55, pp. 10871115
 [DOI]
[PDF]
 Modeling population structure under
hierarchical Dirichlet processes, with K. Adhikari, M. De Iorio, L.
Elliott and Y.W. Teh

Bayesian Analysis, 2019, vol. 14, pp. 313339
 [DOI]
 A characterization of productform
exchangeable feature probability functions, with M. Battiston, D.M. Roy
and Y.W. Teh
 Annals
of Applied Probability,
2018, vol. 28, pp. 14231448
 [DOI]
[PDF]
 Moderate deviations for EwensPitman
sampling models, with S. Feng and F. Gao
 Sankhya
Series A, 2018, vol. 80, pp. 330341
 [DOI]
 Posterior representations of
hierarchical completely random measures in trait allocation models, with
T. Broderick, F. Camerlenghi and L. Masoero
 Advances
in Neural Information Processing Systems, 2018
 [NeurIPS]
 On a general Maclaurin's inequality,
with S.G. Walker
 Proceedings
of the American Mathematical Society, 2018, vol. 146, pp.
175188
 [DOI]
 "Sufficientness" postulates for
Gibbstype priors and hierarchial generalizations, with S. Bacallado, M.
Battiston and L. Trippa
 Statistical
Science, 2017, vol. 32, pp. 487500
 [DOI]
[PDF]
 A marginal sampler for sigmastable PoissonKingman mixture models,
with M. Lomeli and Y.W. Teh
 Journal
of Computational and Graphical Statistics, 2017, vol. 26, pp.
4453
 [DOI]
 Bayesian nonparametric ordination for
the analysis of microbial communities, with S. Bacallado, S. Holmes, B.
Ren and L. Trippa
 Journal
of the American Statistical Association, 2017, vol. 112, pp.
14301442
 [DOI]
 Bayesian nonparametric inference for
discovery probabilities: credible intervals and large sample
asymptotics, with J. Arbel, B. Nipoti and Y.W. Teh
 Statistica
Sinica, 2017, vol. 27, pp. 839858
 [DOI]
 On the stickbreaking representation
for homogeneous NRMIs, with A. Lijoi, B. Nipoti, I. Pruenster and Y.W.
Teh
 Bayesian Analysis, 2016, vol.
11, pp. 697724
 [DOI]
[PDF]
 Rediscovery of GoodTuring estimators
via Bayesian nonparametrics, with B. Nipoti and Y.W. Teh
 Biometrics,
2016, vol. 72, pp. 136145
 [DOI]
 A note on nonparametric inference for
species variety with Gibbstype priors, with L.F. James
 Electronic Journal of Statistics, 2015,
vol. 9, pp. 28842902
 [DOI]
[PDF]
 Frequency of frequencies distributions
and sizedependent exchangeable random partitions, with S.G. Walker and
M. Zhou
 Journal
of the American Statistical Association, 2017, vol. 112, pp.
16231635
 [DOI]
 Relatives of the Ewens sampling formula
in Bayesian nonparametrics, with L.F. James
 Statistical
Science, 2016, vol. 31, pp. 3033
 [DOI]
 Random variate generation for
Laguerretype exponentially tilted alphastable distributions, with B.
Nipoti and Y.W. Teh
 Electronic Journal of Statistics, 2015,
vol. 9, pp. 12301242
 [DOI]
[PDF]
 Large deviation principles for the
EwensPitman sampling model, with S. Feng
 Electronic
Journal of Probability, 2015,
vol. 20, pp. 127
 [DOI]
[PDF]
 Bayesian regularization of the length of memory in reversible
sequences, with S. Bacallado, L. Trippa
 Journal
of the Royal Statistical Society Series B, 2016, vol. 78, pp.
933946
 [DOI]
 Lookingbackward probabilities for Gibbstype exchangeable random
partitions, with S. Bacallado and L. Trippa
 Bernoulli, 2015, vol. 21, pp.
137
 [DOI]
[PDF]
 A hybrid sampler for PoissonKingman
mixture models, with M. Lomeli and Y.W. Teh
 Advances
in Neural Information Processing Systems, 2015
 [NeurIPS]
 On the stickbreaking representation of
sigmastable PoissonKingman models, with M. Lomeli, B. Nipoti and Y.W.
Teh
 Electronic Journal of Statistics,
2014, vol. 8, pp. 10631085
 [DOI]
[PDF]
 Bayesian nonparametric analysis of reversible Markov chains, with S.
Bacallado and L. Trippa
 Annals of Statistics, 2013, vol.
41, pp. 870896
 [DOI]
[PDF]
 Posterior analysis of rare variants in
Gibbstype species sampling models, with O. Cesari and B. Nipoti
 Journal of Multivariate Analysis,
2014, vol. 131, pp. 7998
 [DOI]
 Asymptotics for the number of blocks in
a conditional EwensPitman sampling model, with S. Feng
 Electronic Journal of Probability,
2014, vol. 19, pp. 115
 [DOI]
[PDF]
 MCMC for normalized random measure mixture models, with Y.W. Teh
 Statistical Science, 2013, vol.
28, pp. 335359
 [DOI]
[PDF]
 A new estimator of the discovery probability, with A. Lijoi and I.
Pruenster
 Biometrics, 2012, vol. 68. pp.
11881196
 [DOI]
 Conditional formulae for Gibbstype exchangeable random partitions,
with A. Lijoi and I. Pruenster
 Annals of Applied Probability,
2013, vol. 23, pp. 17211754
 [DOI]
[PDF]
 On the stickbreaking representation of normalized inverse Gaussian
priors, with A. Lijoi and I. Pruenster
 Biometrika, 2012, vol. 99, pp.
663674
 [DOI]
 Slice sampling sigmastable PoissonKingman mixture models, with S.G.
Walker
 Journal of Computational and
Graphical Statistics, 2013, vol. 22, pp. 830847
 [DOI]
 Alphadiversity processes and normalized inverse Gaussian diffusions,
with M. Ruggiero and S.G. Walker
 Annals of Applied Probability,
2013, vol. 23, pp. 386425
 [DOI]
[PDF]
 Asymptotics for a Bayesian nonparametric estimator of species
richness, with A. Lijoi and I. Pruenster
 Bernoulli, 2012, vol. 18, pp.
12671283
 [DOI]
[PDF]
 A class of normalized random measure with an exact predictive sampling
scheme, with L. Trippa
 Scandinavian Journal of Statistics,
2012, vol. 39, pp. 444460
 [DOI]
 A class of measurevalued Markov chains and Bayesian nonparametrics,
with A. Guglielmi and S.G. Walker
 Bernoulli, 2012, vol. 18, pp.
10021030
 [DOI]
[PDF]
 On a generalized ChuVandermonde identity, with I. Pruenster and S.G.
Walker
 Statistics and Probability Letters,
2012, vol. 14, pp. 253262
 [DOI]
 On a class of distributions on the simplex, with G. Hadjicharalambous
and I. Pruenster
 Journal of Statistical Planning and
Inference, 2011, vol. 141, pp. 29873004
 [DOI]
 On a class of random probability measures with a general predictive
structure, with I. Pruenster and S.G. Walker
 Scandinavian Journal of Statistics,
2011, vol. 38, pp. 359376
 [DOI]
 A class of neutral to the right priors induced by superposition of
beta processes, with P. De Blasi and P. Muliere
 Journal of Statistical Planning and
Inference, 2010, vol. 140, pp. 15631575
 [DOI]
 On the distribution of sums of exponential random variables via Wilk's
integral representation, with S.G. Walker
 Acta Applicandae Mathematicae,
2010, vol. 109, pp. 10351042
 [DOI]
 Bayesian nonparametric inference for
species variety with a two parameter PoissonDirichlet process prior,
with A. Lijoi, R.H. Mena and I. Pruenster
 Journal of the Royal Statistical
Society Series B, 2009, vol. 71 pp. 9921008
 [DOI]
 A Gibbssampler based random process in Bayesian nonparametrics, with
M. Ruggiero and S.G. Walker
 Electronic Journal of Statistics,
2009, vol. 3, pp. 15571567
 [DOI]
[PDF]
 A generalized constructive definition for the Dirichlet process, with
S.G. Walker
 Statistics and Probability Letters,
2008, vol. 78, pp. 28362838
 [DOI]
2. Conference
proceedings and other publications
 Infinitechannel deep Stable convolutional neural networks, with D. Bracale, S. Fortini and S. Peluchetti
 Workshop on "Bayesian Deep Learning" at NeurIPS, 2021
 [DOI]
 On Johnson's "sufficientness" postulates for feature sampling models, with F. Camerlenghi
 Mathematics  A festschrift for Eugenio Regazzini's 75th birthday , to appear
 [DOI]
 A compound Poisson perspective of EwensPitman sampling model, with E. Dolera
 Mathematics  A festschrift for Eugenio Regazzini's 75th birthday , to appear
 [DOI]
 Upscaling human activity data: an
ecological perspective, with M. Formentin, A. Maritan, S. Stivanello, S.
Suweis and A. Tovo
 PLoS
ONE, to appear
 [DOI]
 Genomic variety prediction via Bayesian
nonparametrics, with T. Broderick, F. Camerlenghi and L. Masoero
 Symposium
on "Advances in Approximate Bayesian Inference", 2019
 [AABI]
 Neural SDE: information propagation
through the lens of diffusion processes, with S. Peluchetti
 Workshop
on "Bayesian Deep Learning" at NeurIPS, 2019
 [NeurIPS]
 Discussion of "Sparse graphs using
exchangeable random measures" by F. Caron and E.B. Fox, with M.
Battiston
 Journal
of the Royal Statistical Society Series B, 2017, vol. 79, pp.
13431344
 [DOI]
 Addendum to "On a general Maclaurin's
inequality" with S.G.Walker
 Proceedings
of the American Mathematical Society, 2018, vol. 146, pp.
22172218
 [DOI]
 Bayesian nonparametric inference for
shared species richness in multiple populations, with S. Bacallado and
L. Trippa
 Journal of Statistical Planning and
Inference  Special issue on
Bayesian nonparametrics , 2015, vol. 166, pp. 1423
 [DOI]
 Bayesian inference on population
structure: from parametric to nonparametric modeling, with M. De Iorio
and Y.W. Teh
 Nonparametric
Bayesian Inference in Biostatistics, 2015, Springer
 [Springer]
 Are Gibbstype priors the most natural generalization of the Dirichlet
process?, with P. De Blasi, A. Lijoi, R.H. Mena, I. Pruenster and M.
Ruggiero
 IEEE Transactions on Pattern
Analysis and Machine Intelligence 
Special issue on Bayesian nonparametrics , 2015, vol. 37, pp.
212229
 [DOI]
 On a class of sigmastable
PoissonKingman models and an effective marginalized sampler, with M.
Lomeli and Y.W. Teh
 Statistics
and Computing  Special issue MCMSki IV , 2015, vol. 25, pp.
6778
 [DOI]
 Discussion of "On simulation and
properties of stable law" by L. Devroye and L.F. James, with B. Nipoti
 Statistical
Methods and Applications, 2014, vol. 23, pp. 365369
 [DOI]
 Two tales about Bayesian nonparametric modeling, with P. De Blasi, A.
Lijoi, R.H. Mena and I. Pruenster
 Workshop on "Bayesian Statistical
Sciences" at JSM, 2012
 [JSM]
 Contributions to the Dirichlet process and related classes of random
probability measures
 Ph.D. Thesis, Dipartimento di
Scienze delle Decisioni, Università Commerciale "L. Bocconi", 2009
 [Università
"L. Bocconi"]
3. Submitted
papers
 Reinforced urn processes indexed by the
vertices of a recombinant binary tree, with D. Ait Aoudia and P. Muliere
Submitted, 2010
 Nearoptimal estimation of the unseen
under regularly varying tail populations, with Z. Naulet
Submitted, 2021
 Scaled process priors for Bayesian nonparametric estimation of the unseen genetic variation, with T. Broderick, F. Camerlenghi and L. Masoero
Submitted, 2021
 Deep Stable neural networks:
largewidth asymptotics and convergence rates, with S. Fortini and S.
Peluchetti
Submitted, 2021
 Learningaugmented countmin sketches via Bayesian nonparametrics, E. Dolera and S. Peluchetti
 Submitted, 2021
 A new approach to posterior contraction
rates via Wasserstein dynamics, with E. Dolera and E. Mainini
Submitted, 2021
 The power of private likelihoodratio tests for goodnessoffit in frequency tables, E. Dolera
Submitted, 2021
 Bayesian nonparametric mixture modeling for temporal dynamics of gender stereotypes, with M. De Iorio, A. Guglielmi, Y. Lifeng
Submitted, 2021
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