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Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model.

, , , , , and . CVPR, page 8670-8679. Computer Vision Foundation / IEEE, (2019)

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Statistical Principles in Image Modeling., , , and . Technometrics, 49 (3): 249-261 (2007)Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?, and . IEEE Trans. Pattern Anal. Mach. Intell., 24 (7): 1001-1006 (2002)Modeling images and textures by minimax entropy., , and . Human Vision and Electronic Imaging, volume 3016 of SPIE Proceedings, page 387-401. SPIE, (1997)Learning Deep Generative Models with Short Run Inference Dynamics., , , , , and . CoRR, (2019)Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns., , , , and . CoRR, (2019)Abstract painting with interactive control of perceptual entropy., and . ACM Trans. Appl. Percept., 10 (1): 5:1-5:21 (2013)Cooperative Training of Descriptor and Generator Networks., , , and . CoRR, (2016)Learning FRAME Models Using CNN Filters for Knowledge Visualization., , and . CoRR, (2015)Object Category Recognition Using Generative Template Boosting., , , , and . EMMCVPR, volume 4679 of Lecture Notes in Computer Science, page 198-212. Springer, (2007)Dynamic Feature Cascade for Multiple Object Tracking with Trackability Analysis., , , and . EMMCVPR, volume 4679 of Lecture Notes in Computer Science, page 350-361. Springer, (2007)