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Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms., , and . AAAI, page 7900-7907. AAAI Press, (2019)Empirical Study of MC-Dropout in Various Astronomical Observing Conditions., , and . CVPR Workshops, page 17-20. Computer Vision Foundation / IEEE, (2019)Probabilistic Variational Bounds for Graphical Models., , and . NIPS, page 1432-1440. (2015)Distributed Estimation, Information Loss and Exponential Families., and . NIPS, page 1098-1106. (2014)Particle-based Variational Inference for Continuous Systems., , and . NIPS, page 826-834. Curran Associates, Inc., (2009)Efficient Bayesian Inference for Dynamically Changing Graphs., , , and . NIPS, page 1441-1448. Curran Associates, Inc., (2007)A Weighted Mini-Bucket Bound for Solving Influence Diagram., , , and . UAI, volume 115 of Proceedings of Machine Learning Research, page 1159-1168. AUAI Press, (2019)Probabilistic Analysis of a Large-Scale Urban Traffic Sensor Data Set., , and . KDD Workshop on Knowledge Discovery from Sensor Data, volume 5840 of Lecture Notes in Computer Science, page 94-114. Springer, (2008)Deep neural networks for precipitation estimation from remotely sensed information., , , , and . CEC, page 1349-1355. IEEE, (2016)Particle Belief Propagation., and . AISTATS, volume 5 of JMLR Proceedings, page 256-263. JMLR.org, (2009)