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Black box variational inference (BBVI) with reparameterization gradients triggered the exploration of divergence measures other than the Kullback-Leibler (KL) divergence, such as alpha divergences.
A stochastic approximation method
Robbins, H. and Monro, S. (1951) · 1951
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Convergence condition of the TAP equation for the infinite-ranged ising spin glass model
Plefka, T. (1982) · 1971
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Solution of ’solvable model of a spin glass’
Thouless, D., Anderson, P. W., and Palmer, R. G. (1977) · 1977
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Second order approximations for probability models
Kappen, H. J. and Wiegerinck, W. (2001) · 1998
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Gradient-based learning applied to document recognition
LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P. (1998) · 1998
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An introduction to variational methods for graphical models
Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., and Saul, L. K. (1999) · 1999
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A theory of mean field approximation
Tanaka, T. (1999) · 1999
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Information geometry of mean-field approximation
Tanaka, T. (2000) · 2000
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Divergence measures and message passing
Minka, T. (2005) · 2005
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Path integrals in quantum mechanics, statistics, polymer physics, and financial markets
Kleinert, H. (2009) · 2009
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Perturbation corrections in approximate inference: Mixture modelling applications
Paquet, U., Winther, O., and Opper, M. (2009) · 2009
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Large-scale machine learning with stochastic gradient descent
Bottou, L. (2010) · 2010
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Differential-geometrical methods in statistics
Amari, S. (2012) · 2012
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Stochastic variational inference
Hoffman, M. D., Blei, D. M., Wang, C., and Paisley, J. W. (2013) · 2013
Cited alongside, same era.
Perturbative corrections for approximate inference in gaussian latent variable models
Opper, M., Paquet, U., and Winther, O. (2013) · 2013
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Fixed-form variational posterior approximation through stochastic line ar regression
Salimans, T. and Knowles, D. A. (2013) · 2013
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Expectation propagation
Opper, M. (2015) · 2015
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Deep exponential families
Ranganath, R., Tang, L., Charlin, L., and Blei, D. (2015) · 2015
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Importance weighted autoencoders
Burda, Y., Grosse, R., and Salakhutdinov, R. (2016) · 2016
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Black-box alpha divergence minimization
Hernandez-Lobato, J., Li, Y., Rowland, M., Bui, T., Hernández-Lobato, D., and Turner, R. (2016) · 2016
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Rényi divergence variational inference
Li, Y. and Turner, R. E. (2016) · 2016
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Hierarchical variational models
Ranganath, R., Tran, D., and Blei, D. (2016) · 2016
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The generalized reparameterization gradient
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Auto-encoding variational Bayes
Kingma, D. P. and Welling, M. (2014) · 2014
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Black box variational inference
Ranganath, R., Gerrish, S., and Blei, D. M. (2014) · 2014
Cited alongside, same era.
Stochastic backpropagation and approximate inference in deep generative models
Rezende, D. J., Mohamed, S., and Wierstra, D. (2014) · 2014
Cited alongside, same era.
Stochastic Structured Variational Inference
Hoffman, M. and Blei, D. (2015) · 2015
Cited alongside, same era.
Ruiz, F., Titsias, M., and Blei, D. (2016) · 2016
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Dynamic word embeddings
Bamler, R. and Mandt, S. (2017) · 2017
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Variational inference via χ \chi upper bound minimization
Dieng, A. B., Tran, D., Ranganath, R., Paisley, J., and Blei, D. M. (2017) · 2017
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