Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective

Ricardo Baptista, Youssef Marzouk, Olivier Zahm

We consider the problem of reducing the dimensions of parameters and data in non-Gaussian Bayesian inference problems. Our goal is to identify an "informed" subspace of the paramet…