Scalable Bayesian inference for time series via divide-and-conquer

Rihui Ou, Lachlan Astfalck, Deborshee Sen +1

Bayesian computational algorithms tend to scale poorly as data size increases. This has motivated divide-and-conquer-based approaches for scalable inference. These divide the data…