Geometry-informed irreversible perturbations for accelerated convergence of Langevin dynamics
Abstract We introduce a novel geometry-informed irreversible perturbation that accelerates convergence of the Langevin algorithm for Bayesian computation. It is well documented that there exist perturbations to the Langevin dynamics that preserve its invariant measure while accelerati...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer US
2022
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| Online Access: | https://hdl.handle.net/1721.1/145563 |