558 citations · 1.1k across the 26 of their papers we have counts for
27 papers
Spatio-temporal estimation of wind speed and wind power using machine learning: predictions, uncertainty and technical potential
Federico Amato, Fabian Guignard, Alina Walch +3
The growth of wind generation capacities in the past decades has shown that wind energy can contribute to the energy transition in many parts of the world. Being highly variable an…
A survey of active learning algorithms for supervised remote sensing image classification
Devis Tuia, Michele Volpi, Loris Copa +2
Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited te…
Uncertainty Quantification in Extreme Learning Machine: Analytical Developments, Variance Estimates and Confidence Intervals
Fabian Guignard, Federico Amato, Mikhail Kanevski
Uncertainty quantification is crucial to assess prediction quality of a machine learning model. In the case of Extreme Learning Machines (ELM), most methods proposed in the literat…
On Feature Selection Using Anisotropic General Regression Neural Network
Federico Amato, Fabian Guignard, Philippe Jacquet +1
The presence of irrelevant features in the input dataset tends to reduce the interpretability and predictive quality of machine learning models. Therefore, the development of featu…
A Novel Framework for Spatio-Temporal Prediction of Environmental Data Using Deep Learning
Federico Amato, Fabian Guignard, Sylvain Robert +1
As the role played by statistical and computational sciences in climate and environmental modelling and prediction becomes more important, Machine Learning researchers are becoming…
Spatio-temporal evolution of global surface temperature distributions
Federico Amato, Fabian Guignard, Vincent Humphrey +1
Climate is known for being characterised by strong non-linearity and chaotic behaviour. Nevertheless, few studies in climate science adopt statistical methods specifically designed…