Fetching the paper…
Reading the bibliography…
The variational autoencoder (VAE) is a popular combination of deep latent variable model and accompanying variational learning technique.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Latent Dirichlet allocation
David M Blei, Andrew Y Ng, and Michael I Jordan · 2003
Earlier work this paper cites.
Stochastic variational inference
Matthew D Hoffman, David M Blei, Chong Wang, and John Paisley · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Human-level concept learning through probabilistic program induction
Brenden M Lake, Ruslan Salakhutdinov, and Joshua B Tenenbaum · 2015
Earlier work this paper cites.
Generating sentences from a continuous space
Samuel R Bowman, Luke Vilnis, Oriol Vinyals, Andrew Dai, Rafal Jozefowicz, and Samy Bengio · 2016
Earlier work this paper cites.
Importance weighted autoencoders
Yuri Burda, Roger Grosse, and Ruslan Salakhutdinov · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Iterative refinement of the approximate posterior for directed belief networks
Devon Hjelm, Ruslan R Salakhutdinov, Kyunghyun Cho, Nebojsa Jojic, Vince Calhoun, and Junyoung Chung · 2016
Earlier work this paper cites.
ELBO surgery: yet another way to carve up the variational evidence lower bound
Matthew D Hoffman and Matthew J Johnson · 2016
Earlier work this paper cites.
Improved variational inference with inverse autoregressive flow
Diederik P Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, and Max Welling · 2016
Cited alongside, same era.
Ladder variational autoencoders
Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, and Ole Winther · 2016
Cited alongside, same era.
Conditional image generation with pixelcnn decoders
Aaron van den Oord, Nal Kalchbrenner, Lasse Espeholt, Oriol Vinyals, Alex Graves, et al · 2016
Cited alongside, same era.
Variational lossy autoencoder
Xi Chen, Diederik P Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2017
Cited alongside, same era.
TopicRNN: A recurrent neural network with long-range semantic dependency
Adji B Dieng, Chong Wang, Jianfeng Gao, and John Paisley · 2017
Cited alongside, same era.
Z-forcing: Training stochastic recurrent networks
Anirudh Goyal ALIAS PARTH Goyal, Alessandro Sordoni, Marc-Alexandre Côté, Nan Rosemary Ke, and Yoshua Bengio · 2017
Inference suboptimality in variational autoencoders
Chris Cremer, Xuechen Li, and David Duvenaud · 2018
Later among the works it cites.
Avoiding latent variable collapse with generative skip models
Adji B Dieng, Yoon Kim, Alexander M Rush, and David M Blei · 2018
Later among the works it cites.
Semi-amortized variational autoencoders
Yoon Kim, Sam Wiseman, Andrew C Miller, David Sontag, and Alexander M Rush · 2018
Later among the works it cites.
On the challenges of learning with inference networks on sparse, high-dimensional data
Rahul Krishnan, Dawen Liang, and Matthew Hoffman · 2018
Later among the works it cites.
Iterative amortized inference
Joseph Marino, Yisong Yue, and Stephan Mandt · 2018
Later among the works it cites.
A hierarchical latent structure for variational conversation modeling
Yookoon Park, Jaemin Cho, and Gunhee Kim · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
β \beta -VAE: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2017
Cited alongside, same era.
A hybrid convolutional variational autoencoder for text generation
Stanislau Semeniuta, Aliaksei Severyn, and Erhardt Barth · 2017
Cited alongside, same era.
Improved variational autoencoders for text modeling using dilated convolutions
Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, and Taylor Berg-Kirkpatrick · 2017
Cited alongside, same era.
InfoVAE: Information maximizing variational autoencoders
Shengjia Zhao, Jiaming Song, and Stefano Ermon · 2017
Cited alongside, same era.
Fixing a broken ELBO
Alexander Alemi, Ben Poole, Ian Fischer, Joshua Dillon, Rif A Saurous, and Kevin Murphy · 2018
Cited alongside, same era.
The mutual autoencoder: Controlling information in latent code representations, 2018
Mary Phuong, Max Welling, Nate Kushman, Ryota Tomioka, and Sebastian Nowozin · 2018
Later among the works it cites.
Wasserstein auto-encoders
Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly, and Bernhard Schoelkopf · 2018
Later among the works it cites.
VAE with a VampPrior
Jakub M. Tomczak and Max Welling · 2018
Later among the works it cites.
Spherical latent spaces for stable variational autoencoders
Jiacheng Xu and Greg Durrett · 2018
Later among the works it cites.