Log-Gaussian gamma processes for training Bayesian neural networks in Raman and CARS spectroscopies

Abstract

We propose an approach utilizing gamma-distributed random variables, coupled with log-Gaussian modeling, to generate synthetic datasets suitable for training neural networks. This addresses the challenge of limited real observations in...