Preferential Subsampling for Stochastic Gradient Langevin Dynamics

1 code implementation • 28 Oct 2022 • Srshti Putcha, Christopher Nemeth, Paul Fearnhead

Stochastic gradient MCMC (SGMCMC) offers a scalable alternative to traditional MCMC, by constructing an unbiased estimate of the gradient of the log-posterior with a small, uniformly-weighted subsample of the data.

Stochastic Gradient MCMC for Nonlinear State Space Models

2 code implementations • 29 Jan 2019 • Christopher Aicher, Srshti Putcha, Christopher Nemeth, Paul Fearnhead, Emily B. Fox

We evaluate our proposed particle buffered stochastic gradient using stochastic gradient MCMC for inference on both long sequential synthetic and minute-resolution financial returns data, demonstrating the importance of this class of methods.

Bayesian Inference Time Series +1