10 citations · 26 across the 17 of their papers we have counts for
5 papers · 1 filter
Deep Stable neural networks: large-width asymptotics and convergence rates
Stefano Favaro, Sandra Fortini, Stefano Peluchetti
In modern deep learning, there is a recent and growing literature on the interplay between large-width asymptotic properties of deep Gaussian neural networks (NNs), i.e. deep NNs w…
Infinite-color randomly reinforced urns with dominant colors
Hristo Sariev, Sandra Fortini, Sonia Petrone
We define and prove limit results for a class of dominant Pólya sequences, which are randomly reinforced urn processes with color-specific random weights and unbounded number of po…
Approximating the Operating Characteristics of Bayesian Uncertainty Directed Trial Designs
Marta Bonsaglio, Sandra Fortini, Steffen Ventz +1
Bayesian response adaptive clinical trials are currently evaluating experimental therapies for several diseases. Adaptive decisions, such as pre-planned variations of the randomiza…
Large-width functional asymptotics for deep Gaussian neural networks
Daniele Bracale, Stefano Favaro, Sandra Fortini +1
In this paper, we consider fully connected feed-forward deep neural networks where weights and biases are independent and identically distributed according to Gaussian distribution…
Infinite-channel deep stable convolutional neural networks
Daniele Bracale, Stefano Favaro, Sandra Fortini +1
The interplay between infinite-width neural networks (NNs) and classes of Gaussian processes (GPs) is well known since the seminal work of Neal (1996). While numerous theoretical r…