Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision

Casting Bayesian inference as a neural network optimization problem targeting an amortized posterior is attractive, as it extends to otherwise intractable statistical models and offers near instantaneous inference for new datasets after prepaying the training cost.