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Black-box alpha (BB-$\alpha$) is a new approximate inference method based on the minimization of $\alpha$-divergences.
Differential-Geometrical Methods in Statistic
Amari, Shun-ichi · 1985
Earlier work this paper cites.
Information geometric measurements of generalisation
Zhu, Huaiyu and Rohwer, Richard · 1995
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Earlier work this paper cites.
An introduction to variational methods for graphical models
Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., and Saul, L. K · 1999
Earlier work this paper cites.
Expectation propagation for approximate inference in dynamic Bayesian networks
Heskes, Tom and Zoeter, Onno · 2002
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Power ep
Minka, Thomas P · 2004
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Lichman, M · 2013
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Kingma, D. P. and Welling, M · 2014
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Adam: A method for stochastic optimization
Kingma, Diederik and Ba, Jimmy · 2014
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Ranganath, Rajesh, Gerrish, Sean, and Blei, David · 2014
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Xu, Minjie, Lakshminarayanan, Balaji, Teh, Yee Whye, Zhu, Jun, and Zhang, Bo · 2014
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Expectation propagation in the large-data limit
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Stochastic expectation propagation
Li, Yingzhen, Hernandez-Lobato, Jose Miguel, and Turner, Richard E · 2015
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Fixed-form variational posterior approximation through stochastic linear regression
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Expectation propagation as a way of life
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Lead candidates for high-performance organic photovoltaics from high-throughput quantum chemistry–the harvard clean energy project
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