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2020 – today
- 2024
[j10]Mario Beraha, Stefano Favaro, Matteo Sesia:
Random measure priors in Bayesian recovery from sketches. J. Mach. Learn. Res. 25: 249:1-249:53 (2024)- [i16]Mario Beraha, Lorenzo Masoero, Stefano Favaro, Thomas S. Richardson:
A Nonparametric Bayes Approach to Online Activity Prediction. CoRR abs/2401.14722 (2024) - [i15]Lorenzo Masoero, Mario Beraha, Thomas S. Richardson, Stefano Favaro:
Improved prediction of future user activity in online A/B testing. CoRR abs/2402.03231 (2024) - [i14]Lucia Pezzetti, Stefano Favaro, Stefano Peluchetti:
Function-Space MCMC for Bayesian Wide Neural Networks. CoRR abs/2408.14325 (2024) - 2023
- [j9]Emanuele Dolera, Stefano Favaro, Stefano Peluchetti:
Learning-augmented count-min sketches via Bayesian nonparametrics. J. Mach. Learn. Res. 24: 12:1-12:60 (2023) - [j8]Matteo Sesia, Stefano Favaro, Edgar Dobriban:
Conformal Frequency Estimation using Discrete Sketched Data with Coverage for Distinct Queries. J. Mach. Learn. Res. 24: 348:1-348:80 (2023) - [i13]Alberto Bordino, Stefano Favaro, Sandra Fortini:
Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions. CoRR abs/2304.04008 (2023) - [i12]Alberto Bordino, Stefano Favaro, Sandra Fortini:
Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities. CoRR abs/2304.04010 (2023) - [i11]Stefano Favaro, Boris Hanin, Domenico Marinucci, Ivan Nourdin, Giovanni Peccati:
Quantitative CLTs in Deep Neural Networks. CoRR abs/2307.06092 (2023) - [i10]Mario Beraha, Stefano Favaro, Matteo Sesia:
Frequency and cardinality recovery from sketched data: a novel approach bridging Bayesian and frequentist views. CoRR abs/2309.15408 (2023) - 2022
- [j7]Alberto Bordino, Stefano Favaro, Sandra Fortini:
Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions. Trans. Mach. Learn. Res. 2022 (2022) - [c6]Matteo Sesia, Stefano Favaro:
Conformal Frequency Estimation with Sketched Data. NeurIPS 2022 - [i9]Stefano Favaro, Sandra Fortini, Stefano Peluchetti:
Neural tangent kernel analysis of shallow α-Stable ReLU neural networks. CoRR abs/2206.08065 (2022) - 2021
- [j6]Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro:
Consistent estimation of small masses in feature sampling. J. Mach. Learn. Res. 22: 6:1-6:28 (2021) - [j5]Stefano Peluchetti, Stefano Favaro:
Doubly infinite residual neural networks: a diffusion process approach. J. Mach. Learn. Res. 22: 175:1-175:48 (2021) - [c5]Emanuele Dolera, Stefano Favaro, Stefano Peluchetti:
A Bayesian nonparametric approach to count-min sketch under power-law data streams. AISTATS 2021: 226-234 - [c4]Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti:
Large-width functional asymptotics for deep Gaussian neural networks. ICLR 2021 - [i8]Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti:
Infinite-channel deep stable convolutional neural networks. CoRR abs/2102.03739 (2021) - [i7]Emanuele Dolera, Stefano Favaro, Stefano Peluchetti:
A Bayesian nonparametric approach to count-min sketch under power-law data streams. CoRR abs/2102.03743 (2021) - [i6]Emanuele Dolera, Stefano Favaro, Stefano Peluchetti:
Learning-augmented count-min sketches via Bayesian nonparametrics. CoRR abs/2102.04462 (2021) - [i5]Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti:
Large-width functional asymptotics for deep Gaussian neural networks. CoRR abs/2102.10307 (2021) - [i4]Stefano Favaro, Sandra Fortini, Stefano Peluchetti:
Deep Stable neural networks: large-width asymptotics and convergence rates. CoRR abs/2108.02316 (2021) - 2020
- [c3]Stefano Peluchetti, Stefano Favaro:
Infinitely deep neural networks as diffusion processes. AISTATS 2020: 1126-1136 - [c2]Stefano Peluchetti, Stefano Favaro, Sandra Fortini:
Stable behaviour of infinitely wide deep neural networks. AISTATS 2020: 1137-1146 - [i3]Stefano Favaro, Sandra Fortini, Stefano Peluchetti:
Stable behaviour of infinitely wide deep neural networks. CoRR abs/2003.00394 (2020) - [i2]Stefano Peluchetti, Stefano Favaro:
Doubly infinite residual networks: a diffusion process approach. CoRR abs/2007.03253 (2020)
2010 – 2019
- 2019
- [i1]Stefano Peluchetti, Stefano Favaro:
Neural Stochastic Differential Equations. CoRR abs/1905.11065 (2019) - 2015
- [j4]Pierpaolo De Blasi, Stefano Favaro, Antonio Lijoi, Ramsés H. Mena
, Igor Prünster, Matteo Ruggiero:
Are Gibbs-Type Priors the Most Natural Generalization of the Dirichlet Process? IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 212-229 (2015) - [j3]Stefano Favaro, Maria Lomeli, Yee Whye Teh:
On a class of σ-stable Poisson-Kingman models and an effective marginalized sampler. Stat. Comput. 25(1): 67-78 (2015) - [c1]Maria Lomeli, Stefano Favaro, Yee Whye Teh:
A hybrid sampler for Poisson-Kingman mixture models. NIPS 2015: 2161-2169 - 2014
- [j2]Oriana Cesari, Stefano Favaro, Bernardo Nipoti:
Posterior analysis of rare variants in Gibbs-type species sampling models. J. Multivar. Anal. 131: 79-98 (2014) - [j1]Stefano Favaro, Bernardo Nipoti:
Discussion of "On simulation and properties of the stable law" by L. Devroye and L. James. Stat. Methods Appl. 23(3): 365-369 (2014)
Coauthor Index
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