Variational Inference: A Review for Statisticians, David M. Blei, Alp Kucukelbir, Jon D. McAuliffe, 2017Journal of the American Statistical Association, Vol. 112 (Taylor & Francis Ltd.)DOI: 10.1080/01621459.2017.1285773 - Provides a comprehensive overview of variational inference, including the limitations of mean-field approximations and an introduction to more advanced methods.
Variational Inference with Normalizing Flows, Danilo Jimenez Rezende, Shakir Mohamed, 2015International Conference on Machine Learning (ICML)DOI: 10.48550/arXiv.1505.05770 - Introduces the concept of normalizing flows for constructing flexible variational distributions, detailing planar and radial flow transformations.
Normalizing Flows for Probabilistic Modeling and Inference, George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan, 2021Journal of Machine Learning Research, Vol. 22 (JMLR, Inc.)DOI: 10.5555/3540209.3540212 - A comprehensive review of normalizing flows, covering their theoretical foundations, various architectures (including autoregressive and coupling flows), and applications in probabilistic modeling and inference.