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A Bayesian Nonparametric Approach to Image Super-Resolution.

, , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 37 (2): 346-358 (2015)

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Probabilistic Topic Models., , and . IEEE Signal Process. Mag., 27 (6): 55-65 (2010)Mixed membership stochastic block models, , , and . Advances in Neural Information Processing Systems (NIPS) 21, Red Hook, NY: Curran Associates, (2009)Mixed membership stochastic block models for relational data, with applications to protein-protein interactions, , , and . Proceedings of International Biometric Society-ENAR Annual Meetings, (2006)Stochastic Gradient Descent as Approximate Bayesian Inference, , and . (2017)cite arxiv:1704.04289Comment: 35 pages, published version (JMLR 2017).Prescribed Generative Adversarial Networks, , , and . (2019)cite arxiv:1910.04302Comment: Code for this paper can be found at https://github.com/adjidieng/PresGANs.Panel Discussion.. SNA@ICML, volume 4503 of Lecture Notes in Computer Science, page 186-194. Springer, (2006)The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling., , , and . ICML, page 1151-1158. Omnipress, (2010)Noisin: Unbiased Regularization for Recurrent Neural Networks., , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 1251-1260. PMLR, (2018)Variational Bayesian Inference with Stochastic Search., , and . ICML, icml.cc / Omnipress, (2012)Stick-Breaking Beta Processes and the Poisson Process., , and . AISTATS, volume 22 of JMLR Proceedings, page 850-858. JMLR.org, (2012)