Pattern Recognition and Machine Learning, Christopher M. Bishop, 2006 (Springer)DOI: 10.1007/978-0-387-45528-0 - Provides a comprehensive and foundational treatment of Variational Inference, including the derivation and algorithm of Coordinate Ascent Variational Inference (CAVI) within the mean-field framework.
Variational Inference: A Review for Statisticians, David M. Blei, Alp Kucukelbir, Jon D. McAuliffe, 2017Journal of the American Statistical Association, Vol. 112 (Taylor & Francis)DOI: 10.1080/01621459.2017.1328493 - An authoritative review paper that provides a broad overview of variational inference, detailing the theoretical underpinnings and practical applications of CAVI.
Probabilistic Machine Learning: Advanced Topics, Kevin Patrick Murphy, 2023 (MIT Press) - Offers an in-depth and contemporary treatment of variational inference, with detailed discussions on the mechanics and application of CAVI.
Latent Dirichlet Allocation, David M. Blei, Andrew Y. Ng, and Michael I. Jordan, 2003Journal of Machine Learning Research, Vol. 3 - This seminal paper applies the mean-field coordinate ascent approach to a probabilistic topic model (Latent Dirichlet Allocation), illustrating the practical implementation and effectiveness of CAVI for complex generative models.