Multi-Relational Learning with Gaussian Processes

59 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep Factors for Forecasting (2019, background): “The global-local structure has been used previously in a number of special contexts (Xu et al., 2009; Ahmadi et al., 2011; Hwang et al., 2016; Choi et al., 2011).”
Gradient-based boosting for statistical relational learning: The relational dependency network case (2011, methodology): “The results of RDN-B are quite similar to the best results reported using multi-relational Gaussian Processes [50], where the AUC for ROC was 0.”
Statistical Relational Artificial Intelligence: Logic, Probability, and Computation (2016, methodology): “Nonparametric relational models have been used for analyzing social networks [Xu et al., 2009a].”
Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series (2016, background): “Finding a shared structure in multiple sequences may reveal the common covariance structures of the sequences beyond the patterns in a single sequence (Chu et al., 2006; Xu et al., 2009; Wilson & Ghahramani, 2011).”