Stefano Favaro

40 papers A* 2A 4Journal 31Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Conformal Classification with New Labels. COPA Tianmin Xie, Ziyi Liang, Stefano Favaro, Matteo Sesia
2025	J	`jnl`	Conformal Inference for Open-Set and Imbalanced Classification. CoRR Tianmin Xie, Yanfei Zhou, Ziyi Liang, Stefano Favaro, Matteo Sesia
2025	A	`conf`	Function-Space MCMC for Bayesian Wide Neural Networks. AISTATS Lucia Pezzetti, Stefano Favaro, Stefano Peluchetti
2025	J	`jnl`	Gaussian credible intervals in Bayesian nonparametric estimation of the unseen. CoRR Claudia Contardi, Emanuele Dolera, Stefano Favaro
2025	J	`jnl`	MCMC for Bayesian Nonparametric Mixture Modeling Under Differential Privacy. J. Comput. Graph. Stat. Mario Beraha, Stefano Favaro, Vinayak Rao
2025	J	`jnl`	Student-t processes as infinite-width limits of posterior Bayesian neural networks. CoRR Francesco Caporali, Stefano Favaro, Dario Trevisan
2024	J	`jnl`	A Nonparametric Bayes Approach to Online Activity Prediction. CoRR Mario Beraha, Lorenzo Masoero, Stefano Favaro, Thomas S. Richardson
2024	J	`jnl`	Function-Space MCMC for Bayesian Wide Neural Networks. CoRR Lucia Pezzetti, Stefano Favaro, Stefano Peluchetti
2024	J	`jnl`	Improved prediction of future user activity in online A/B testing. CoRR Lorenzo Masoero, Mario Beraha, Thomas S. Richardson, Stefano Favaro
2024	J	`jnl`	Large-width asymptotics and training dynamics of α-Stable ReLU neural networks. Trans. Mach. Learn. Res. Stefano Favaro, Sandra Fortini, Stefano Peluchetti
2024	—	`conf`	Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities. AABI Alberto Bordino, Stefano Favaro, Sandra Fortini
2024	J	`jnl`	Random measure priors in Bayesian recovery from sketches. J. Mach. Learn. Res. Mario Beraha, Stefano Favaro, Matteo Sesia
2023	J	`jnl`	Conformal Frequency Estimation using Discrete Sketched Data with Coverage for Distinct Queries. J. Mach. Learn. Res. Matteo Sesia, Stefano Favaro, Edgar Dobriban
2023	J	`jnl`	Frequency and cardinality recovery from sketched data: a novel approach bridging Bayesian and frequentist views. CoRR Mario Beraha, Stefano Favaro, Matteo Sesia
2023	J	`jnl`	Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions. CoRR Alberto Bordino, Stefano Favaro, Sandra Fortini
2023	J	`jnl`	Learning-augmented count-min sketches via Bayesian nonparametrics. J. Mach. Learn. Res. Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
2023	J	`jnl`	Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities. CoRR Alberto Bordino, Stefano Favaro, Sandra Fortini
2023	J	`jnl`	Quantitative CLTs in Deep Neural Networks. CoRR Stefano Favaro, Boris Hanin, Domenico Marinucci, Ivan Nourdin, Giovanni Peccati
2022	A*	`conf`	Conformal Frequency Estimation with Sketched Data. NeurIPS Matteo Sesia, Stefano Favaro
2022	J	`jnl`	Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions. Trans. Mach. Learn. Res. Alberto Bordino, Stefano Favaro, Sandra Fortini
2022	J	`jnl`	Neural tangent kernel analysis of shallow α-Stable ReLU neural networks. CoRR Stefano Favaro, Sandra Fortini, Stefano Peluchetti
2021	A	`conf`	A Bayesian nonparametric approach to count-min sketch under power-law data streams. AISTATS Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
2021	J	`jnl`	A Bayesian nonparametric approach to count-min sketch under power-law data streams. CoRR Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
2021	J	`jnl`	Consistent estimation of small masses in feature sampling. J. Mach. Learn. Res. Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro
2021	J	`jnl`	Deep Stable neural networks: large-width asymptotics and convergence rates. CoRR Stefano Favaro, Sandra Fortini, Stefano Peluchetti
2021	J	`jnl`	Doubly infinite residual neural networks: a diffusion process approach. J. Mach. Learn. Res. Stefano Peluchetti, Stefano Favaro
2021	J	`jnl`	Infinite-channel deep stable convolutional neural networks. CoRR Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti
2021	A*	`conf`	Large-width functional asymptotics for deep Gaussian neural networks. ICLR Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti
2021	J	`jnl`	Large-width functional asymptotics for deep Gaussian neural networks. CoRR Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti
2021	J	`jnl`	Learning-augmented count-min sketches via Bayesian nonparametrics. CoRR Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
2020	J	`jnl`	Doubly infinite residual networks: a diffusion process approach. CoRR Stefano Peluchetti, Stefano Favaro
2020	A	`conf`	Infinitely deep neural networks as diffusion processes. AISTATS Stefano Peluchetti, Stefano Favaro
2020	A	`conf`	Stable behaviour of infinitely wide deep neural networks. AISTATS Stefano Peluchetti, Stefano Favaro, Sandra Fortini
2020	J	`jnl`	Stable behaviour of infinitely wide deep neural networks. CoRR Stefano Favaro, Sandra Fortini, Stefano Peluchetti
2019	J	`jnl`	Neural Stochastic Differential Equations. CoRR Stefano Peluchetti, Stefano Favaro
2015	—	`conf`	A hybrid sampler for Poisson-Kingman mixture models. NIPS Maria Lomeli, Stefano Favaro, Yee Whye Teh
2015	J	`jnl`	Are Gibbs-Type Priors the Most Natural Generalization of the Dirichlet Process? IEEE Trans. Pattern Anal. Mach. Intell. Pierpaolo De Blasi, Stefano Favaro, Antonio Lijoi, Ramsés H. Mena, Igor Prünster, Matteo Ruggiero
2015	J	`jnl`	On a class of σ-stable Poisson-Kingman models and an effective marginalized sampler. Stat. Comput. Stefano Favaro, Maria Lomeli, Yee Whye Teh
2014	J	`jnl`	Discussion of "On simulation and properties of the stable law" by L. Devroye and L. James. Stat. Methods Appl. Stefano Favaro, Bernardo Nipoti
2014	J	`jnl`	Posterior analysis of rare variants in Gibbs-type species sampling models. J. Multivar. Anal. Oriana Cesari, Stefano Favaro, Bernardo Nipoti