Exact Gaussian processes for massive datasets via non-stationary sparsity-discovering kernels
Exact Gaussian processes for massive datasets via non-stationary sparsity-discovering kernels
A Gaussian Process (GP) is a prominent mathematical framework for stochastic function approximation in science and engineering applications. Its success is largely attributed to the GP's analytical tractability, robustness, and natural inclusion of uncertainty quantification. Unfortunately, the use of exact GPs is prohibitively expensive for large datasets due to their …