98 citations · 196 across the 32 of their papers we have counts for
37 papers
Transformed Samplers with Variance Reduction
Siran Liu, Michalis Tisias, Petros Dellaportas
Markov chain Monte Carlo (MCMC) methods are the standard tool for computing expectations under complex probability distributions. Control variates reduce the variance of the result…
Fraud Detection via Bayesian Positive-Unlabeled Learning with Gaussian Processes and Multilayer Networks
Konstantinos Bourazas, Angelos Alexopoulos, Petros Dellaportas +1
Tax fraud remains a central challenge for public revenue authorities worldwide, imposing fiscal losses estimated to reach up to 1 trillion euros annually in the EU alone. Fraudulen…
Multi-task Neural Diffusion Processes
Joseph Rawson, Domniki Ladopoulou, Petros Dellaportas
Neural diffusion processes provide a scalable, non-Gaussian approach to modelling distributions over functions, but existing formulations are limited to single-task inference and d…
Probabilistic Wind Power Modelling via Heteroscedastic Non-Stationary Gaussian Processes
Domniki Ladopoulou, Dat Minh Hong, Petros Dellaportas
Accurate probabilistic prediction of wind power is crucial for maintaining grid stability and facilitating the efficient integration of renewable energy sources. Gaussian process (…
Multi-Horizon Echo State Network Prediction of Intraday Stock Returns
Giovanni Ballarin, Jacopo Capra, Petros Dellaportas
Stock return prediction is a problem that has received much attention in the finance literature. In recent years, sophisticated machine learning procedures have been shown to perfo…
Variance Reduction for Independent Metropolis
Siran Liu, Petros Dellaportas, Michalis K. Titsias
Assume that we would like to estimate the expected value of a function with respect to an intractable density , which is specified up to some unknown normalising constant. W…