3 papers
stat.ML2026
Kriging via variably scaled kernels
Gianluca Audone, Francesco Marchetti, Emma Perracchione +1
Classical Gaussian processes and Kriging models are commonly based on stationary kernels, whereby correlations between observations depend exclusively on the relative distance betw…
math.NA2024
A Recipe for Learning Variably Scaled Kernels via Discontinuous Neural Networks
Gianluca Audone, Francesco Della Santa, Emma Perracchione +1
The efficacy of interpolating via Variably Scaled Kernels (VSKs) is known to be dependent on the definition of a proper scaling function, but no numerical recipes to construct it a…
physics.space-ph2024
Forecasting Geoffective Events from Solar Wind Data and Evaluating the Most Predictive Features through Machine Learning Approaches
Sabrina Guastavino, Katsiaryna Bahamazava, Emma Perracchione +8
This study addresses the prediction of geomagnetic disturbances by exploiting machine learning techniques. Specifically, the Long-Short Term Memory recurrent neural network, which…