3 papers
stat.CO2025
Scalable Fitting Methods for Multivariate Gaussian Additive Models with Covariate-dependent Covariance Matrices
Vincenzo Gioia, Matteo Fasiolo, Ruggero Bellio +1
We propose efficient computational methods to fit multivariate Gaussian additive models, where the mean vector and the covariance matrix are allowed to vary with covariates, in an…
cs.LG2021
Daily peak electrical load forecasting with a multi-resolution approach
Yvenn Amara-Ouali, Matteo Fasiolo, Yannig Goude +1
In the context of smart grids and load balancing, daily peak load forecasting has become a critical activity for stakeholders of the energy industry. An understanding of peak magni…
stat.CO2016
Langevin Incremental Mixture Importance Sampling
Matteo Fasiolo, Flávio Eler de Melo, Simon Maskell
This work proposes a novel method through which local information about the target density can be used to construct an efficient importance sampler. The backbone of the proposed me…