Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows

Fat tails make both density estimation and variational inference difficult. The authors develop an alternative theory for tail parameter estimation in normalizing flows, prove that tail parameters are estimable at a faster rate than location/scale, and introduce anisotropic tail-adaptive flows (ATAF) that provably match fat-tailed target distributions.