1 citations · 1 across the 4 of their papers we have counts for
8 papers
Merging of Bayes and quasi-Bayes empirical Bayes procedures for Poisson compound decisions
Stefano Favaro, Sandra Fortini
The Poisson compound decision problem is a long-standing problem in statistics, in which empirical Bayes methods are used to estimate Poisson means under a mixture model. We study…
Quasi-Bayes empirical Bayes estimation of sums of random variables
Stefano Favaro, Sandra Fortini
The estimation of sums of functions of observable and unobservable variables is a long-standing problem in statistics with applications across many domains. Empirical Bayes methods…
Quasi-Bayes empirical Bayes: a sequential approach to the Poisson compound decision problem
Stefano Favaro, Sandra Fortini
The Poisson compound decision problem is a long-standing problem is statistics, for which empirical Bayes methods are commonly used to estimate Poisson means in static or batch set…
Quasi-Bayes properties of a recursive procedure for mixtures
Sandra Fortini, Sonia Petrone
Bayesian methods are often optimal, yet increasing pressure for fast computations, especially with streaming data, brings renewed interest in faster, possibly sub-optimal, solution…
Uncertainty Decomposition for Bayes-Filtered Transformers via Bayesian Predictive Inference
Sandra Fortini, Kenyon Ng, Sonia Petrone +2
Bayes-filtered transformers are transformers meta-learned on sequences from a prior predictive distribution to approximate the corresponding posterior predictive distribution. They…
Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities
Alberto Bordino, Stefano Favaro, Sandra Fortini
There is a recent and growing literature on large-width asymptotic and non-asymptotic properties of deep Gaussian neural networks (NNs), namely NNs with weights initialized as Gaus…