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We propose a novel neural topic model in the Wasserstein autoencoders (WAE) framework.
Lagging inference networks and posterior collapse in variational autoencoders
Junxian He, Daniel Spokoyny, Graham Neubig, and Taylor Berg-Kirkpatrick. 2019 · 1901
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Information diffusion kernels
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Mallet: A machine learning for language toolkit
Andrew Kachites McCallum. 2002 · 2002
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Latent dirichlet allocation
David M. Blei, Andrew Y. Ng, Michael I. Jordan, and John Lafferty. 2003 · 2003
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Finding scientific topics
T. L. Griffiths and M. Steyvers. 2004 · 2004
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Hierarchical topic models and the nested chinese restaurant process
Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum, and David M. Blei. 2004 · 2004
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Visualizing high-dimensional data using t-sne
L.J.P.V.D. Maaten and GE Hinton. 2008 · 2008
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Online learning for latent dirichlet allocation
Matthew Hoffman, Francis R. Bach, and David M. Blei. 2010 · 2010
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Software Framework for Topic Modelling with Large Corpora
Radim Řehůřek and Petr Sojka. 2010 · 2010
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A kernel two-sample test
Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Schölkopf, and Alexander Smola. 2012 · 2012
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Evaluating topic coherence using distributional semantics
Nikolaos Aletras and Mark Stevenson. 2013 · 2013
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Representation learning: A review and new perspectives
Y Bengio, Aaron Courville, and Pascal Vincent. 2013 · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling. 2013 · 2013
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Dbpedia - a large-scale, multilingual knowledge base extracted from wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N. Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick van Kleef, Sören Auer, and Christian Bizer. 2013 · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
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Machine reading tea leaves: Automatically evaluating topic coherence and topic model quality
Jey Han Lau, David Newman, and Timothy Baldwin. 2014 · 2014
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UCI machine learning repository
Dua Dheeru and Efi Karra Taniskidou. 2017 · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville. 2017 · 2017
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Adversarially regularized autoencoders
Yoon Kim, Kelly Zhang, Alexander M Rush, Yann LeCun, et al. 2017 · 2017
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Mmd gan: Towards deeper understanding of moment matching network
Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, and Barnabás Póczos. 2017 · 2017
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Autoencoding variational inference for topic models
Akash Srivastava and Charles Sutton. 2017 · 2017
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Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, and Brendan Frey. 2015 · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Generating sentences from a continuous space
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, and Samy Bengio. 2016 · 2016
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Pointer sentinel mixture models
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Neural variational inference for text processing
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou. 2017 · 2017
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Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly, and Bernhard Schoelkopf. 2017 · 2017
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Coherence-aware neural topic modeling
Ran Ding, Ramesh Nallapati, and Bing Xiang. 2018 · 2018
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Semi-amortized variational autoencoders
Yoon Kim, Sam Wiseman, Andrew Miller, David Sontag, and Alexander Rush. 2018 · 2018
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On the latent space of wasserstein auto-encoders
Paul K Rubenstein, Bernhard Schoelkopf, and Ilya Tolstikhin. 2018 · 2018
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Atm: Adversarial-neural topic model
Rui Wang, Deyu Zhou, and Yulan He. 2018 · 2018
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