98 citations · 196 across the 32 of their papers we have counts for
6 papers · 1 filter
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 (…
A Bayesian framework for genome-wide inference of DNA methylation levels
Marcel Hirt, Axel Finke, Alexandros Beskos +4
DNA methylation is an important epigenetic mark that has been studied extensively for its regulatory role in biological processes and diseases. WGBS allows for genome-wide measurem…
Missing data patterns in runners' careers: do they matter?
Mattia Stival, Mauro Bernardi, Manuela Cattelan +1
Predicting the future performance of young runners is an important research issue in experimental sports science and performance analysis. We analyse a data set with annual seasona…
Doubly-online changepoint detection for monitoring health status during sports activities
Mattia Stival, Mauro Bernardi, Petros Dellaportas
We provide an online framework for analyzing data recorded by smart watches during running activities. In particular, we focus on identifying variations in the behavior of one or m…
Flexible marked spatio-temporal point processes with applications to event sequences from association football
Santhosh Narayanan, Ioannis Kosmidis, Petros Dellaportas
We develop a new family of marked point processes by focusing the characteristic properties of marked Hawkes processes exclusively to the space of marks, providing the freedom to s…
Bayesian forecasting of mortality rates using latent Gaussian models
Angelos Alexopoulos, Petros Dellaportas, Jonathan J. Forster
We provide forecasts for mortality rates by using two different approaches. First we employ dynamic non-linear logistic models based on Heligman-Pollard formula. Second, we assume…