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Particle Filtering for Nonparametric Bayesian Matrix Factorization.

, and . NIPS, page 1513-1520. MIT Press, (2006)

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Inference Networks for Sequential Monte Carlo in Graphical Models., and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 3040-3049. JMLR.org, (2016)The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling., , and . AISTATS, volume 33 of JMLR Workshop and Conference Proceedings, page 660-668. JMLR.org, (2014)Black-Box Policy Search with Probabilistic Programs., , , and . AISTATS, volume 51 of JMLR Workshop and Conference Proceedings, page 1195-1204. JMLR.org, (2016)Nonparametric Bayesian Models for Neural Data.. Brown University, USA, (2007)Particle Gibbs with Ancestor Sampling for Probabilistic Programs., , , and . AISTATS, volume 38 of JMLR Workshop and Conference Proceedings, JMLR.org, (2015)A New Approach to Probabilistic Programming Inference., , and . AISTATS, volume 33 of JMLR Workshop and Conference Proceedings, page 1024-1032. JMLR.org, (2014)Discovering natural kinds of robot sensory experiences in unstructured environments., , and . J. Field Robotics, 23 (11-12): 1077-1089 (2006)Deplump for Streaming Data., and . DCC, page 363-372. IEEE Computer Society, (2011)Inference Compilation and Universal Probabilistic Programming., , and . AISTATS, volume 54 of Proceedings of Machine Learning Research, page 1338-1348. PMLR, (2017)Maximum a Posteriori Estimation by Search in Probabilistic Programs., and . SOCS, page 201-205. AAAI Press, (2015)