Speaker
Kilian Scheutwinkel
(University of Cambridge)
Description
PolySwyft is an implementation of a sequential simulation-based nested sampler by merging two algorithms that are commonly used for Bayesian inference: PolyChord and swyft. PolySwyft uses the NRE functionality of swyft and generates a new joint training dataset with PolyChord to iteratively estimate more accurate posterior distributions. PolySwyft can be terminated using pre-defined rounds similar to swyft or be executed in an automated mode using a KL-divergence termination criterion between current posterior estimates. We demonstrate the capabilities of PolySwyft on multimodal toy problems where the ground truth posterior is known.
Primary author
Kilian Scheutwinkel
(University of Cambridge)
Co-authors
Dr
Christoph Weniger
(University of Amsterdam)
Eloy de Lera Acedo
(University of Cambridge)
Will Handley
(University Of Cambridge)
