5 citations · 8 across the 3 of their papers we have counts for
3 papers
Latent Variable Multi-output Gaussian Processes for Hierarchical Datasets
Chunchao Ma, Arthur Leroy, Mauricio Alvarez
Multi-output Gaussian processes (MOGPs) have been introduced to deal with multiple tasks by exploiting the correlations between different outputs. Generally, MOGPs models assume a…
Cluster-Specific Predictions with Multi-Task Gaussian Processes
Arthur Leroy, Pierre Latouche, Benjamin Guedj +1
A model involving Gaussian processes (GPs) is introduced to simultaneously handle multi-task learning, clustering, and prediction for multiple functional data. This procedure acts…
MAGMA: Inference and Prediction with Multi-Task Gaussian Processes
Arthur Leroy, Pierre Latouche, Benjamin Guedj +1
A novel multi-task Gaussian process (GP) framework is proposed, by using a common mean process for sharing information across tasks. In particular, we investigate the problem of ti…