Scholar
Stefano Favaro
Google Scholar ID: UjIKIf8AAAAJ
University of Torino and Collegio Carlo Alberto
Citations & Impact
Citations
1,184
H-index
18
i10-index
37
Publications
20
Co-authors
44
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Main publications:
- 1. Function-space MCMC for Bayesian wide neural networks, with L. Pezzetti and S. Peluchetti, Artificial Intelligence and Statistics, 2025.
- 2. A smoothed-Bayesian approach to frequency recovery from sketched data, with M. Beraha and M. Sesia, Journal of the American Statistical Association, to appear.
- 3. On the power of private likelihood-ratio tests for goodness-of-fit in frequency tables, with M. Beraha and E. Dolera, Bernoulli, to appear.
- 4. Quantitative central limit theorems in deep neural networks, with B. Hanin, D. Marinucci, I. Nourdin and G. Peccati, Probability Theory and Related Fields, 2025.
- 5. Random measure priors in Bayesian recovery from sketches, with M. Beraha and M. Sesia, Journal of Machine Learning Research, 2024.
- 6. MCMC for Bayesian nonparametric mixture modeling under differential privacy, with M. Beraha and V. Rao, Journal of Computational and Graphical Statistics, to appear.
- 7. Preconditioned Crank-Nicolson algorithms for Bayesian wide neural networks, with S. Peluchetti and L. Pezzetti, Neural Information Processing Systems, 2024.
- 8. A martingale approach to Gaussian fluctuations and laws of iterated logarithm for Ewens-Pitman model, with B. Bercu, Stochastic Processes and their Applications, 2024.
- 9. Bayesian nonparametric inference for 'species-sampling' problems, with C. Balocchi and Z. Naulet, Statistical Science, to appear.
- 10. On second-order Poincaré inequalities in non-asymptotic approximation of Gaussian neural networks, with A. Bordino and S. Fortini, Advances in Approximate Bayesian Inference, 2024.
- 11. Large-width asymptotics and training dynamics for alpha-Stable ReLU neural networks, with S. Fortini and S. Peluchetti, Journal of Machine Learning Research, 2024.
- 12. Wasserstein posterior contraction rates in non-dominated Bayesian nonparametric models, with E. Dolera and E. Mainini, Annales de l'Institut Henri Poincaré - Probabilités et Statistiques, to appear.
- 13. Scaled process priors for Bayesian nonparametric estimation of the unseen genetic variation, with T. Broderick, F. Camerlenghi and L. Masoero, Journal of the American Statistical Association, 2024.
- 14. Strong posterior contraction rates via Wasserstein dynamics, with E. Dolera and E. Mainini, Probability Theory and Related Fields, 2024.
- 15. A Bayesian nonparametric approach to species sampling problems with ordering, with C. Balocchi and F. Camerlenghi, Bayesian Analysis, to appear.
- 16. Bayesian nonparametric mixture modeling for temporal dynamics of gender stereotypes, with M. De Iorio, A. Guglielmi and Y. Lifeng, Annals of Applied Statistics, 2023.
- 17. Near-optimal estimation of the unseen under regularly varying tail populations, with Z. Naulet, Bernoulli, 2023.
- 18. Conformal frequency estimation using discrete sketched data with coverage for distinct queries, with E. Dobriban and M. Sesia, Journal of Machine Learning Research, 2023.
Research Experience
- Professor of Statistics, Università di Torino; Carlo Alberto Chair of Statistics and Machine Learning, Collegio Carlo Alberto; Department of Economic-Social and Mathematical-Statistical Sciences, University of Turin.
Background
- Research interests: nonparametric Bayes and empirical Bayes methods, statistical machine learning, data confidentiality and fairness, learning-augmented recovery algorithms, mathematics of deep learning.
