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Continual repeated annealed flow transport Monte Carlo

Abstract:

We propose Continual Repeated Annealed Flow Transport Monte Carlo (CRAFT), a method that combines a sequential Monte Carlo (SMC) sampler (itself a generalization of Annealed Importance Sampling) with variational inference using normalizing flows. The normalizing flows are directly trained to transport between annealing temperatures using a KL divergence for each transition. This optimization objective is itself estimated using the normalizing flow/SMC approximation. We show conceptually and u...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publication website:
https://proceedings.mlr.press/v162/matthews22a.html

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Oxford college:
Hertford College
Role:
Author
ORCID:
0000-0002-7662-419X
Publisher:
Journal of Machine Learning Research Publisher's website
Host title:
Proceedings of the 39th International Conference on Machine Learning
Series:
Proceedings of Machine Learning Research
Series number:
162
Pages:
15196-15219
Publication date:
2022-06-22
Acceptance date:
2022-05-14
Event title:
39th International Conference on Machine Learning (ICML 2022)
Event location:
Baltimore, Maryland, USA
Event website:
https://icml.cc/Conferences/2022
Event start date:
2022-07-17
Event end date:
2022-07-23
ISSN:
2640-3498
Language:
English
Keywords:
Pubs id:
1312349
Local pid:
pubs:1312349
Deposit date:
2022-12-08

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