Least squares variational inference
Least Squares Variational Inference (LSVI) is a gradient-free method for fixed-point recursion in exponential families. It performs ordinary least squares regression on tempered log-target evaluations under a variational approximation. This scheme avoids inverting the Fisher information matrix for Gaussian distributions, offering efficient complexity and competitive performance compared to standard methods.