Training Normalizing Flows with Computationally Intensive Target Probability Distributions

The author argues that using the REINFORCE algorithm for gradient estimation in normalizing flows can significantly improve training efficiency by avoiding complex gradient calculations, as demonstrated in the 2D Schwinger model.