Stefano Peluchetti

According to our database, Stefano Peluchetti authored at least 16 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Learning-augmented count-min sketches via Bayesian nonparametrics.

Emanuele Dolera, Stefano Favaro, Stefano Peluchetti

J. Mach. Learn. Res., 2023

Non-Denoising Forward-Time Diffusions.

Stefano Peluchetti

CoRR, 2023

Diffusion Bridge Mixture Transports, Schrödinger Bridge Problems and Generative Modeling.

Stefano Peluchetti

CoRR, 2023

2022

Learning Stochastic Optimal Policies via Gradient Descent.

Stefano Massaroli, Michael Poli, Stefano Peluchetti, Jinkyoo Park, Atsushi Yamashita, Hajime Asama

IEEE Control. Syst. Lett., 2022

Neural tangent kernel analysis of shallow α-Stable ReLU neural networks.

Stefano Favaro, Sandra Fortini, Stefano Peluchetti

CoRR, 2022

2021

Doubly infinite residual neural networks: a diffusion process approach.

Stefano Peluchetti, Stefano Favaro

J. Mach. Learn. Res., 2021

Deep Stable neural networks: large-width asymptotics and convergence rates.

Stefano Favaro, Sandra Fortini, Stefano Peluchetti

CoRR, 2021

Infinite-channel deep stable convolutional neural networks.

Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti

CoRR, 2021

Large-width functional asymptotics for deep Gaussian neural networks.

Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti

Proceedings of the 9th International Conference on Learning Representations, 2021

A Bayesian nonparametric approach to count-min sketch under power-law data streams.

Emanuele Dolera, Stefano Favaro, Stefano Peluchetti

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Doubly infinite residual networks: a diffusion process approach.

Stefano Peluchetti, Stefano Favaro

CoRR, 2020

Stable behaviour of infinitely wide deep neural networks.

Stefano Peluchetti, Stefano Favaro, Sandra Fortini

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Infinitely deep neural networks as diffusion processes.

Stefano Peluchetti, Stefano Favaro

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

An empirical study of pretrained representations for few-shot classification.

Tiago Ramalho, Thierry Sousbie, Stefano Peluchetti

CoRR, 2019

Neural Stochastic Differential Equations.

Stefano Peluchetti, Stefano Favaro

CoRR, 2019

2013

The strong weak convergence of the quasi-EA.

Stefano Peluchetti, Gareth O. Roberts, Bruno Casella

Queueing Syst. Theory Appl., 2013