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Spatio-temporal video autoencoder with differentiable memory. arXiv preprint arXiv:1511.06309 ( 2015 ). Viorica Patraucean, Ankur Handa, and Roberto Cipolla. 2015. Spatio-temporal video autoencoder with differentiable memory. arXiv preprint arXiv:1511.06309 (2015)."},{"key":"e_1_3_2_2_32_1","volume-title":"Unsupervised Learning of Sequence Representations by Autoencoders. arXiv preprint arXiv:1804.00946","author":"Pei Wenjie","year":"2018","unstructured":"Wenjie Pei and David MJ Tax . 2018. Unsupervised Learning of Sequence Representations by Autoencoders. arXiv preprint arXiv:1804.00946 ( 2018 ). Wenjie Pei and David MJ Tax. 2018. Unsupervised Learning of Sequence Representations by Autoencoders. arXiv preprint arXiv:1804.00946 (2018)."},{"key":"e_1_3_2_2_33_1","volume-title":"A neural autoencoder approach for document ranking and query refinement in pharmacogenomic information retrieval","author":"Pfeiffer Jonas","unstructured":"Jonas Pfeiffer , Samuel Broscheit , Rainer Gemulla , and Mathias G\u00f6schl . 2018. A neural autoencoder approach for document ranking and query refinement in pharmacogenomic information retrieval . Association for Computational Linguistics . Jonas Pfeiffer, Samuel Broscheit, Rainer Gemulla, and Mathias G\u00f6schl. 2018. A neural autoencoder approach for document ranking and query refinement in pharmacogenomic information retrieval. Association for Computational Linguistics."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-31750-2_3"},{"key":"e_1_3_2_2_35_1","volume-title":"Nonlinear dimensionality reduction by locally linear embedding. science","author":"Roweis Sam T","year":"2000","unstructured":"Sam T Roweis and Lawrence K Saul . 2000. Nonlinear dimensionality reduction by locally linear embedding. science , Vol. 290 , 5500 ( 2000 ), 2323--2326. Sam T Roweis and Lawrence K Saul. 2000. Nonlinear dimensionality reduction by locally linear embedding. science, Vol. 290, 5500 (2000), 2323--2326."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2008.11.006"},{"key":"e_1_3_2_2_37_1","volume-title":"International conference on machine learning. 843--852","author":"Srivastava Nitish","year":"2015","unstructured":"Nitish Srivastava , Elman Mansimov , and Ruslan Salakhudinov . 2015 . Unsupervised learning of video representations using lstms . 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