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Deep latent variable models, trained using variational autoencoders or generative adversarial networks, are now a key technique for representation learning of continuous structures.
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Optimal transport: old and new , volume 338
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Extracting and Composing Robust Features with Denoising Autoencoders
Vincent, P., Larochelle, H., Bengio, Y., and Manzagol, P.-A · 2008
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Transport Inequalities. A Survey
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Contractive Auto-Encoders: Explicit Invariance During Feature Extraction
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Linguistic Regularities in Continuous Space Word Representations
Mikolov, T., tau Yih, S. W., and Zweig, G · 2013
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Generative adversarial nets
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Auto-Encoding Variational Bayes
Kingma, D. P. and Welling, M · 2014
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Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Rezende, D. J., Mohamed, S., and Wierstra, D · 2014
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A large annotated corpus for learning natural language inference
Bowman, S. R., Angeli, G., Potts, C., and Manning., C. D · 2015
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Semi-supervised sequence learning
Dai, A. M. and Le, Q. V · 2015
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Makhzani, A., Shlens, J., Jaitly, N., Goodfellow, I., and Frey, B · 2015
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Character-level Convolutional Networks for Text Classification
Zhang, X., Zhao, J., and LeCun, Y · 2015
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Generating Sentences from a Continuous Space
Bowman, S. R., Vilnis, L., Vinyals, O., Dai, A. M., Jozefowicz, R., and Bengio, S · 2016
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Learning distributed representations of sentences from unlabelled data
Hill, F., Cho, K., and Korhonen, A · 2016
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GANs for Sequences of Discrete Elements with the Gumbel-Softmax Distribution
Kusner, M. and Hernandez-Lobato, J. M · 2016
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Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Radford, A., Metz, L., and Chintala, S · 2016
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A note on the evaluation of generative models
Theis, L., van den Oord, A., and Bethge, M · 2016
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Towards Principled Methods for Training Generative Adversarial Networks
Arjovsky, M. and Bottou, L · 2017
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Wasserstein GAN
Arjovsky, M., Chintala, S., and Bottou, L · 2017
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Maximum-Likelihood Augment Discrete Generative Adversarial Networks
Che, T., Li, Y., Zhang, R., Hjelm, R. D., Li, W., Song, Y., and Bengio, Y · 2017
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Variational Lossy Autoencoder
Chen, X., Kingma, D. P., Salimans, T., Duan, Y., Dhariwal, P., Schulman, J., Sutskever, I., and Abbeel, P · 2017
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Unsupervised learning of disentangled representations from video
Denton, E. and Birodkar, V · 2017
Adversarial Generation of Natural Language
Rajeswar, S., Subramanian, S., Dutil, F., Pal, C., and Courville, A · 2017
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A Hybrid Convolutional Variational Autoencoder for Text Generation
Semeniuta, S., Severyn, A., and Barth, E · 2017
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Style Transfer from Non-Parallel Text by Cross-Alignment
Shen, T., Lei, T., Barzilay, R., and Jaakkola, T · 2017
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Adversarially Learned Inference
Vincent Dumoulin, Ishmael Belghazi, B. P. O. M. A. L. M. A. A. C · 2017
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Improved Variational Autoencoders for Text Modeling using Dilated Convolutions
Yang, Z., Hu, Z., Salakhutdinov, R., and Berg-Kirkpatrick, T · 2017
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SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
Yu, L., Zhang, W., Wang, J., and Yu, Y · 2017
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TopicRNN: A Recurrent Neural Network With Long-Range Semantic Dependency
Dieng, A. B., Wang, C., Gao, J., , and Paisley, J · 2017
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Adversarial Feature Learning
Donahue, J., Krahenbühl, P., and Darrell, T · 2017
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Improved Training of Wasserstein GANs
Gulrajani, I., Ahmed, F., Arjovsky, M., and Vincent Dumoulin, A. C · 2017
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Generating Sentences by Editing Prototypes
Guu, K., Hashimoto, T. B., Oren, Y., and Liang, P · 2017
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Controllable Text Generation
Hu, Z., Yang, Z., Liang, X., Salakhutdinov, R., and Xing, E. P · 2017
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Categorical Reparameterization with Gumbel-Softmax
Jang, E., Gu, S., and Poole, B · 2017
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Eval all, trust a few, do wrong to none: Comparing sentence generation models
Cífka, O., Severyn, A., Alfonseca, E., and Filippova, K · 2018
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Boundary-Seeking Generative Adversarial Networks
Hjelm, R. D., Jacob, A. P., Che, T., Cho, K., and Bengio, Y · 2018
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On Unifying Deep Generative Models
Hu, Z., Yang, Z., Salakhutdinov, R., and Xing, E. P · 2018
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Semi-Amortized Variational Autoencoders
Kim, Y., Wiseman, S., Miller, A. C., Sontag, D., and Rush, A. M · 2018
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Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer
Li, J., Jia, R., He, H., and Liang, P · 2018
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Spectral Normalization For Generative Adversarial Networks
Miyato, T., Kataoka, T., Koyama, M., and Yoshida, Y · 2018
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Style Transfer Through Back-Translation
Prabhumoye, S., Tsvetkov, Y., Salakhutdinov, R., and Black, A. W · 2018
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Wasserstein Auto-Encoders
Tolstikhin, I., Bousquet, O., Gelly, S., and Schoelkopf, B · 2018
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VAE with a VampPrior
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Topic Compositional Neural Language Model
Wang, W., Gan, Z., Wang, W., Shen, D., Huang, J., Ping, W., Satheesh, S., and Carin, L · 2018
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Unsupervised Text Style Transfer using Language Models as Discriminators
Yang, Z., Hu, Z., Dyer, C., Xing, E. P., and Berg-Kirkpatrick, T · 2018
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