155 citations · 173 across the 18 of their papers we have counts for
7 papers · 1 filter
Correlated Product of Experts for Sparse Gaussian Process Regression
Manuel Schürch, Dario Azzimonti, Alessio Benavoli +1
Gaussian processes (GPs) are an important tool in machine learning and statistics with applications ranging from social and natural science through engineering. They constitute a p…
Choice functions based multi-objective Bayesian optimisation
Alessio Benavoli, Dario Azzimonti, Dario Piga
In this work we introduce a new framework for multi-objective Bayesian optimisation where the multi-objective functions can only be accessed via choice judgements, such as ``I pick…
Gaussian Processes to speed up MCMC with automatic exploratory-exploitation effect
Alessio Benavoli, Jason Wyse, Arthur White
We present a two-stage Metropolis-Hastings algorithm for sampling probabilistic models, whose log-likelihood is computationally expensive to evaluate, by using a surrogate Gaussian…
Bayesian Optimisation for Sequential Experimental Design with Applications in Additive Manufacturing
Mimi Zhang, Andrew Parnell, Dermot Brabazon +1
Bayesian optimization (BO) is an approach to globally optimizing black-box objective functions that are expensive to evaluate. BO-powered experimental design has found wide applica…
Quantum indistinguishability through exchangeable desirable gambles
Alessio Benavoli, Alessandro Facchini, Marco Zaffalon
Two particles are identical if all their intrinsic properties, such as spin and charge, are the same, meaning that no quantum experiment can distinguish them. In addition to the we…
Bayesian Kernelised Test of (In)dependence with Mixed-type Variables
Alessio Benavoli, Cassio de Campos
A fundamental task in AI is to assess (in)dependence between mixed-type variables (text, image, sound). We propose a Bayesian kernelised correlation test of (in)dependence using a…