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Generative Adversarial Nets., , , , , , , and . NIPS, page 2672-2680. (2014)EmoNets: Multimodal deep learning approaches for emotion recognition in video., , , , , , , , , and 8 other author(s). J. Multimodal User Interfaces, 10 (2): 99-111 (2016)An Investigation of Model-Free Planning., , , , , , , , , and 3 other author(s). ICML, volume 97 of Proceedings of Machine Learning Research, page 2464-2473. PMLR, (2019)Generalizable Features From Unsupervised Learning., , and . ICLR (Workshop), OpenReview.net, (2017)Multi-Prediction Deep Boltzmann Machines., , , and . NIPS, page 548-556. (2013)Challenges in Representation Learning: A Report on Three Machine Learning Contests., , , , , , , , , and 18 other author(s). ICONIP (3), volume 8228 of Lecture Notes in Computer Science, page 117-124. Springer, (2013)Combining modality specific deep neural networks for emotion recognition in video., , , , , , , , , and 17 other author(s). ICMI, page 543-550. ACM, (2013)Maxout Networks., , , , and . ICML (3), volume 28 of JMLR Workshop and Conference Proceedings, page 1319-1327. JMLR.org, (2013)Theano: A Python framework for fast computation of mathematical expressions, , , , , , , , , and 103 other author(s). (2016)cite arxiv:1605.02688Comment: 19 pages, 5 figures.Conditional generative adversarial nets, and . arXiv preprint arXiv:1411.1784, (2014)