Adaptive Stepsizing for Stochastic Gradient Langevin Dynamics in Bayesian Neural Networks

Rajit Rajpal, Benedict Leimkuhler, Yuanhao Jiang

Bayesian neural networks (BNNs) require scalable sampling algorithms to approximate posterior distributions over parameters. Existing stochastic gradient Markov Chain Monte Carlo (…