Stefano Peluchetti

29 papers A* 1A 4Journal 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Sparser, Faster, Lighter Transformer Language Models. CoRR Edoardo Cetin, Stefano Peluchetti, Emilio Castillo, Akira Naruse, Mana Murakami, Llion Jones
2025	J	`jnl`	BM Trans. Mach. Learn. Res. Stefano Peluchetti
2025	A	`conf`	Function-Space MCMC for Bayesian Wide Neural Networks. AISTATS Lucia Pezzetti, Stefano Favaro, Stefano Peluchetti
2025	J	`jnl`	Latent Discrete Diffusion Models. CoRR Dario Shariatian, Alain Durmus, Stefano Peluchetti
2024	J	`jnl`	BM CoRR Stefano Peluchetti
2024	J	`jnl`	Function-Space MCMC for Bayesian Wide Neural Networks. CoRR Lucia Pezzetti, Stefano Favaro, Stefano Peluchetti
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
2023	J	`jnl`	Diffusion Bridge Mixture Transports, Schrödinger Bridge Problems and Generative Modeling. CoRR Stefano Peluchetti
2023	J	`jnl`	Diffusion Bridge Mixture Transports, Schrödinger Bridge Problems and Generative Modeling. J. Mach. Learn. Res. Stefano Peluchetti
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-Denoising Forward-Time Diffusions. CoRR Stefano Peluchetti
2022	J	`jnl`	Learning Stochastic Optimal Policies via Gradient Descent. IEEE Control. Syst. Lett. Stefano Massaroli, Michael Poli, Stefano Peluchetti, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
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`	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 Stochastic Optimal Policies via Gradient Descent. CoRR Stefano Massaroli, Michael Poli, Stefano Peluchetti, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
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`	An empirical study of pretrained representations for few-shot classification. CoRR Tiago Ramalho, Thierry Sousbie, Stefano Peluchetti
2019	J	`jnl`	Neural Stochastic Differential Equations. CoRR Stefano Peluchetti, Stefano Favaro
2013	J	`jnl`	The strong weak convergence of the quasi-EA. Queueing Syst. Theory Appl. Stefano Peluchetti, Gareth O. Roberts, Bruno Casella