2021
Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference
IROS 2021poster
Gaussian processes (GPs) are a well-known nonparametric Bayesian inference technique, but they suffer from scalability problems for large sample sizes, and their performance can degrade for non-stationary or spatially heterogeneous data. In this work, we seek to overcome these issues through (i) emp…