Expectation Propagation (Minka, 2001) is a widely successful algorithm for variational inference.
Reading the bibliography…
Expectation propagation for neural networks with sparsity-promoting priors
Jylänki, P., Nummenmaa, A., and Vehtari, A. (2014) · 1901
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Best constants in Young’s inequality, its converse, and its generalization to more than three functions
Brascamp, H. J. and Lieb, E. H. (1976) · 1976
Earlier work this paper cites.
On-line Learning in Neural Networks
Opper, M. (1998) · 1998
Earlier work this paper cites.
Expectation Propagation for approximate Bayesian inference
Minka, T. P. (2001) · 2001
Earlier work this paper cites.
Convex Optimization
Boyd, S. and Vandenberghe, L. (2004) · 2004
Earlier work this paper cites.
Assessing Approximate Inference for Binary Gaussian Process Classification
Kuss, M. and Rasmussen, C. E. (2005) · 2005
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Divergence Measures and Message Passing
Minka, T. (2005) · 2005
Earlier work this paper cites.
Expectation Consistent Approximate Inference
Opper, M. and Winther, O. (2005) · 2005
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Expectation Propagation for Exponential Families
Seeger, M. (2005) · 2005
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Numerical Optimization (Springer Series in Operations Research and Financial Engineering)
Nocedal, J. and Wright, S. (2006) · 2006
Earlier work this paper cites.
Simple and globally convergent methods for accelerating the convergence of any em algorithm
Varadhan, R. and Roland, C. (2008) · 2008
Cited alongside, same era.
Graphical Models, Exponential Families, and Variational Inference (Foundations and Trends(r) Machine Learning)
Wainwright, M. J. and Jordan, M. I. (2008) · 2008
Cited alongside, same era.
Perturbation Corrections in Approximate Inference: Mixture Modelling Applications
Paquet, U., Winther, O., and Opper, M. (2009) · 2009
Cited alongside, same era.
Approximate bayesian inference for latent gaussian models by using integrated nested laplace approximations
Rue, H., Martino, S., and Chopin, N. (2009) · 2009
Cited alongside, same era.
Pattern Recognition and Machine Learning (Information Science and Statistics)
Bishop, C. M. (2007) · 2011
Cited alongside, same era.
Robust gaussian process regression with a student-t likelihood
Jylänki, P., Vanhatalo, J., and Vehtari, A. (2011) · 2011
Cited alongside, same era.
Expectation propagation with factorizing distributions: A gaussian approximation and performance results for simple models
Ribeiro, F. and Opper, M. (2011) · 2011
Cited alongside, same era.
The em algorithm, variational approximations and expectation propagation for mixtures
Titterington, D. M. (2011) · 2011
Cited alongside, same era.
The bernstein-von-mises theorem under misspecification
Kleijn, B., van der Vaart, A., et al. (2012) · 2012
Cited alongside, same era.
Expectation Propagation for Nonlinear Inverse Problems - with an Application to Electrical Impedance Tomography
Gehre, M. and Jin, B. (2013) · 2013
Cited alongside, same era.
Expectation propagation for likelihood-free inference
Barthelmé, S. and Chopin, N. (2014) · 2014
Later among the works it cites.
Expectation propagation as a way of life
Gelman, A., Vehtari, A., Jylänki, P., Robert, C., Chopin, N., and Cunningham, J. P. (2014) · 2014
Later among the works it cites.
Expectation propagation
Raymond, J., Manoel, A., and Opper, M. (2014) · 2014
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PAC-Bayesian AUC classification and scoring
Ridgway, J., Alquier, P., Chopin, N., and Liang, F. (2014) · 2014
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Log-concavity and strong log-concavity: A review
Saumard, A. and Wellner, J. A. (2014) · 2014
Later among the works it cites.
Distributed bayesian posterior sampling via moment sharing
Xu, M., Lakshminarayanan, B., Teh, Y. W., Zhu, J., and Zhang, B. (2014) · 2014
Later among the works it cites.
Bounding errors of Expectation-Propagation
Dehaene, G. P. and Barthelmé, S. (2015) · 2015
Closest in time.
Stochastic Expectation Propagation
Li, Y., Hernández-Lobato, J. M., and Turner, R. E. (2015) · 2015
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Approximating Bayesian confidence regions in convex inverse problems
Pereyra, M. (2016) · 2016
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Approximations for Binary Gaussian Process Classification
Nickisch, H. and Rasmussen, C. E. (2008) · 2078
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