5 papers
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 methods have been shown to perform…
Probabilistic Multi-Layer Perceptrons for Wind Farm Condition Monitoring
Filippo Fiocchi, Domna Ladopoulou, Petros Dellaportas
We provide a condition monitoring system for wind farms, based on normal behaviour modelling using a probabilistic multi-layer perceptron with transfer learning via fine-tuning. Th…
Variance Reduction for the Independent Metropolis Sampler
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.…