Fetching the paper…
Reading the bibliography…
In this paper, we study recent neural generative models for text generation related to variational autoencoders.
Markov processes over denumerable products of spaces, describing large systems of automata
Leonid Nisonovich Vaserstein. 1969 · 1969
Earlier work this paper cites.
Animating rotation with quaternion curves
Ken Shoemake. 1985 · 1985
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Building Natural Language Generation Systems
Ehud Reiter and Robert Dale. 2000 · 2000
Earlier work this paper cites.
Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton. 2008 · 2008
Earlier work this paper cites.
Overcoming the lack of parallel data in sentence compression
Katja Filippova and Yasemin Altun. 2013 · 2013
Earlier work this paper cites.
Auto-encoding variational Bayes
Diederik P. Kingma and Max Welling. 2013 · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Semi-supervised sequence learning
Andrew M. Dai and Quoc V. Le. 2015 · 2015
Earlier work this paper cites.
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, and Ian J. Goodfellow. 2015 · 2015
Cited alongside, same era.
Generating sentences from a continuous space
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Józefowicz, and Samy Bengio. 2016 · 2016
Cited alongside, same era.
Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, and Pieter Abbeel. 2016 · 2016
Cited alongside, same era.
A theoretically grounded application of dropout in recurrent neural networks
Yarin Gal and Zoubin Ghahramani. 2016 · 2016
Cited alongside, same era.
Neural machine translation in linear time
Nal Kalchbrenner, Lasse Espeholt, Karen Simonyan, Aäron van den Oord, Alex Graves, and Koray Kavukcuoglu. 2016 · 2016
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loic Barrault, and Antoine Bordes. 2017 · 2017
Later among the works it cites.
Generating sentences by editing prototypes
Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, and Percy Liang. 2017 · 2017
Later among the works it cites.
GANs trained by a two time-scale update rule converge to a local Nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter. 2017 · 2017
Later among the works it cites.
Toward controlled generation of text
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P. Xing. 2017 · 2017
Later among the works it cites.
Unsupervised machine translation using monolingual corpora only
Guillaume Lample, Ludovic Denoyer, and Marc’Aurelio Ranzato. 2017 · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Improved techniques for training GANs
Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen. 2016 · 2016
Cited alongside, same era.
Variational neural machine translation
Biao Zhang, Deyi Xiong, and Jinsong Su. 2016 · 2016
Cited alongside, same era.
Unsupervised neural machine translation
Mikel Artetxe, Gorka Labaka, Eneko Agirre, and Kyunghyun Cho. 2017 · 2017
Cited alongside, same era.
From optimal transport to generative modeling: the VEGAN cookbook
Olivier Bousquet, Sylvain Gelly, Ilya Tolstikhin, Carl-Johann Simon-Gabriel, and Bernhard Schoelkopf. 2017 · 2017
Cited alongside, same era.
Adversarially regularized autoencoders for generating discrete structures
Junbo Jake Zhao, Yoon Kim, Kelly Zhang, Alexander M. Rush, and Yann LeCun. 2017a
Cited in the paper.
Learning discourse-level diversity for neural dialog models using conditional variational autoencoders
Tiancheng Zhao, Ran Zhao, and Maxine Eskénazi. 2017b
Cited in the paper.
Later among the works it cites.
Are GANs created equal? A large-scale study
Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, and Olivier Bousquet. 2017 · 2017
Later among the works it cites.
A hybrid convolutional variational autoencoder for text generation
Stanislau Semeniuta, Aliaksei Severyn, and Erhardt Barth. 2017 · 2017
Later among the works it cites.
Improved variational autoencoders for text modeling using dilated convolutions
Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, and Taylor Berg-Kirkpatrick. 2017 · 2017
Later among the works it cites.