Preprint
Oct 2026
Neural Simulation-Based Inference for space-time Gaussian processes
This work proposes two neural network architectures - Neural Bayes Estimation (NBE) and Neural Ratio Estimation (NRE) - to learn the parameters of Gaussian spatio-temporal Gneiting-Mat{\'e}rn models with advection, and adopts a sliding-window approach to achieve fully amortized inference.
Alexandre Loret, Lucia Clarotto, N. Desassis et al.
· 0 citations