1![Learning to Pass Expectation Propagation Messages Nicolas Heess∗ Gatsby Unit, UCL Daniel Tarlow Microsoft Research Learning to Pass Expectation Propagation Messages Nicolas Heess∗ Gatsby Unit, UCL Daniel Tarlow Microsoft Research](https://www.pdfsearch.io/img/48a3acf3d7bf9e11511fa31db49a0dbb.jpg) | Add to Reading ListSource URL: papers.nips.ccLanguage: English - Date: 2014-11-25 16:15:37
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2![Just-In-Time Kernel Regression for Expectation Propagation Wittawat Jitkrittum1 Arthur Gretton1 Nicolas Heess∗ S. M. Ali Eslami∗ Just-In-Time Kernel Regression for Expectation Propagation Wittawat Jitkrittum1 Arthur Gretton1 Nicolas Heess∗ S. M. Ali Eslami∗](https://www.pdfsearch.io/img/5103342d6dfef6d80867a0d7ce0785ea.jpg) | Add to Reading ListSource URL: arkitus.comLanguage: English - Date: 2016-01-08 16:47:19
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3![Mean Field Variational Approximations in Continuous-Time Markov Processes A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Mean Field Variational Approximations in Continuous-Time Markov Processes A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science](https://www.pdfsearch.io/img/01c12f9ea4ac34ba43b736074ec930cd.jpg) | Add to Reading ListSource URL: www.cs.huji.ac.ilLanguage: English - Date: 2015-08-10 08:23:20
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4![On the concentration of expectation and approximate inference in layered networks Michael I. Jordan University of California Berkeley, CA 94720 On the concentration of expectation and approximate inference in layered networks Michael I. Jordan University of California Berkeley, CA 94720](https://www.pdfsearch.io/img/70470fb4bab0d4b5a137cdd28c79565f.jpg) | Add to Reading ListSource URL: dept.stat.lsa.umich.eduLanguage: English - Date: 2004-01-18 19:14:54
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5![Derivation of Expectation Propagation for “Fast Gaussian Process Methods for Point Process Intensity Estimation” John P. Cunningham Department of Electrical Engineering, Stanford University, Stanford, CA 94305 Derivation of Expectation Propagation for “Fast Gaussian Process Methods for Point Process Intensity Estimation” John P. Cunningham Department of Electrical Engineering, Stanford University, Stanford, CA 94305](https://www.pdfsearch.io/img/c2707c7b35fc33015fc132438faa95ea.jpg) | Add to Reading ListSource URL: stat.columbia.eduLanguage: English - Date: 2013-08-24 16:54:12
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6![Expectation propagation for infinite mixtures (Extended abstract) Thomas Minka and Zoubin Ghahramani December 17, 2003 Abstract This note describes a method for approximate inference in infinite models that uses determin Expectation propagation for infinite mixtures (Extended abstract) Thomas Minka and Zoubin Ghahramani December 17, 2003 Abstract This note describes a method for approximate inference in infinite models that uses determin](https://www.pdfsearch.io/img/9ddada55f56ece30e231f2396699d7c2.jpg) | Add to Reading ListSource URL: mlg.eng.cam.ac.ukLanguage: English - Date: 2006-05-16 12:30:01
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7![Expectation Propagation in the large-data limit Guillaume Dehaene, Simon Barthelmé 1st April 2016 arXiv:1503.08060v2 [stat.CO] 31 Mar 2016 Expectation Propagation in the large-data limit Guillaume Dehaene, Simon Barthelmé 1st April 2016 arXiv:1503.08060v2 [stat.CO] 31 Mar 2016](https://www.pdfsearch.io/img/0c0e4958c9b5e1cc2d538d9549be699d.jpg) | Add to Reading ListSource URL: arxiv.orgLanguage: English - Date: 2016-03-31 21:25:59
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8![Hierarchical expectation propagation for Bayesian aggregation of average data Andrew Gelman, Columbia University Sebastian Weber, Novartis also Bob Carpenter, Daniel Lee, Frédéric Bois, Aki Vehtari, and Amy Racine Hierarchical expectation propagation for Bayesian aggregation of average data Andrew Gelman, Columbia University Sebastian Weber, Novartis also Bob Carpenter, Daniel Lee, Frédéric Bois, Aki Vehtari, and Amy Racine](https://www.pdfsearch.io/img/4b6bed4b75c9c156c5b683e555a6cc38.jpg) | Add to Reading ListSource URL: www.stat.columbia.eduLanguage: English - Date: 2015-09-23 11:37:16
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9![TO APPEAR IN PROC. OF 2014 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING, 2014 EXPECTATION PROPAGATION FOR NONSTATIONARY HETEROSCEDASTIC GAUSSIAN PROCESS REGRESSION Ville Tolvanen1 , Pasi Jyl¨an TO APPEAR IN PROC. OF 2014 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING, 2014 EXPECTATION PROPAGATION FOR NONSTATIONARY HETEROSCEDASTIC GAUSSIAN PROCESS REGRESSION Ville Tolvanen1 , Pasi Jyl¨an](https://www.pdfsearch.io/img/7ded8d8ad44dfad8f32cc2bafdd5d68e.jpg) | Add to Reading ListSource URL: becs.aalto.fiLanguage: English - Date: 2014-07-25 07:13:09
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10![Hybrid Variational/Gibbs Collapsed Inference in Topic Models Max Welling∗ Dept. Computer Science University of California Irvine Irvine, CA, USA Hybrid Variational/Gibbs Collapsed Inference in Topic Models Max Welling∗ Dept. Computer Science University of California Irvine Irvine, CA, USA](https://www.pdfsearch.io/img/b7a82d0c15afc8af8098019657931e9d.jpg) | Add to Reading ListSource URL: www.ics.uci.eduLanguage: English - Date: 2008-05-14 13:35:04
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