Showing stat.MLShow all
2 papers · 1 filter
stat.ML2026
Spatio-temporal probabilistic forecast using MMAF-guided learning
Leonardo Bardi, Imma Valentina Curato, Lorenzo Proietti
We present a theory-guided generalized Bayesian methodology for spatio-temporal raster data, which we use to train an ensemble of stochastic feed-forward neural networks with Gauss…
stat.ML2023
Mixed moving average field guided learning for spatio-temporal data
Imma Valentina Curato, Orkun Furat, Lorenzo Proietti +1
Influenced mixed moving average fields are a versatile modeling class for spatio-temporal data. However, their predictive distribution is not generally known. Under this modeling a…