Bayesian Tensor Completion and Gaussian Processes: Functional Universality and Rank Learning

This ArXiv article explores a combination of Bayesian Tensor Completion and Multioutput Gaussian Processes. The paper likely investigates improved methods for handling missing data in complex, multi-dimensional datasets, particularly focusing on functional relationships.

• •Focuses on methods for handling missing data in high-dimensional datasets.
• •Combines Bayesian Tensor Completion with Multioutput Gaussian Processes.
• •Emphasizes functional universality and rank learning.