Christopher Nemeth

Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates

2023 · arXiv (Cornell University)

In recent years, particle-based variational inference (ParVI) methods such as Stein variational gradient descent (SVGD) have grown in popularity as scalable methods for Bayesian inference. Unfortunately, the properties of such methods invariably depend on hyperparameters …