A Simple and Robust Multi-Fidelity Data Fusion Method for Effective Modeling of Citizen-Science Air Pollution Data
A robust multi-fidelity Gaussian process that combines sparse, high-quality reference monitors with dense but noisy citizen-science sensors, using a Huber loss to bound the influence of contaminated data. Submitted to the Annals of Applied Statistics.