Search Results for author:
Found 2 papers, 1 papers with code
Light curve completion and forecasting using fast and scalable Gaussian processes (MuyGPs)
In particular, a single light curve can feature hundreds of thousands of observations, which is well beyond the practical realization limits of a conventional GP on a single machine.
Reinforcement Learning via Gaussian Processes with Neural Network Dual Kernels
While deep neural networks (DNNs) and Gaussian Processes (GPs) are both popularly utilized to solve problems in reinforcement learning, both approaches feature undesirable drawbacks for challenging problems.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
