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VAEs (Variational AutoEncoders) have proved to be powerful in the context of density modeling and have been used in a variety of contexts for creative purposes.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
Methods of information geometry
S.-i. Amari and H. Nagaoka · 2007
Earlier work this paper cites.
Learning deep architectures for AI
Y. Bengio et al · 2009
Earlier work this paper cites.
music21: A toolkit for computer-aided musicology and symbolic music data
M. S. Cuthbert and C. Ariza · 2010
Earlier work this paper cites.
Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol · 2010
Earlier work this paper cites.
Elements of information theory
T. M. Cover and J. A. Thomas · 2012
Earlier work this paper cites.
Auto-encoding variational Bayes
D. P. Kingma and M. Welling · 2013
Earlier work this paper cites.
Variational recurrent auto-encoders
O. Fabius and J. R. van Amersfoort · 2014
Earlier work this paper cites.
Learning longer memory in recurrent neural networks
T. Mikolov, A. Joulin, S. Chopra, M. Mathieu, and M. Ranzato · 2014
Earlier work this paper cites.
Generating sentences from a continuous space
S. R. Bowman, L. Vilnis, O. Vinyals, A. M. Dai, R. Józefowicz, and S. Bengio · 2015
Earlier work this paper cites.
A recurrent latent variable model for sequential data
J. Chung, K. Kastner, L. Dinh, K. Goel, A. C. Courville, and Y. Bengio · 2015
Cited alongside, same era.
Reducing overfitting in deep networks by decorrelating representations
M. Cogswell, F. Ahmed, R. Girshick, L. Zitnick, and D. Batra · 2015
Cited alongside, same era.
DRAW: A recurrent neural network for image generation
K. Gregor, I. Danihelka, A. Graves, D. Jimenez Rezende, and D. Wierstra · 2015
Cited alongside, same era.
Autoencoding beyond pixels using a learned similarity metric
A. B. L. Larsen, S. K. Sønderby, H. Larochelle, and O. Winther · 2015
Cited alongside, same era.
A. Makhzani, J. Shlens, N. Jaitly, I. Goodfellow, and B. Frey · 2015
Sequential neural models with stochastic layers
M. Fraccaro, S. K. Sønderby, U. Paquet, and O. Winther · 2016
Later among the works it cites.
Deep Learning
I. Goodfellow, Y. Bengio, and A. Courville · 2016
Later among the works it cites.
DeepBach: a steerable model for Bach chorales generation
G. Hadjeres, F. Pachet, and F. Nielsen · 2016
Later among the works it cites.
Zoneout: Regularizing rnns by randomly preserving hidden activations
D. Krueger, T. Maharaj, J. Kramár, M. Pezeshki, N. Ballas, N. R. Ke, A. Goyal, Y. Bengio, H. Larochelle, A. Courville, et al · 2016
Later among the works it cites.
Discriminative regularization for generative models
A. Lamb, V. Dumoulin, and A. Courville · 2016
Later among the works it cites.
Assisted lead sheet composition using FlowComposer
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Learning structured output representation using deep conditional generative models
K. Sohn, H. Lee, and X. Yan · 2015
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Attribute2Image: Conditional image generation from visual attributes
X. Yan, J. Yang, K. Sohn, and H. Lee · 2015
Cited alongside, same era.
Information geometry and its applications
S.-i. Amari · 2016
Cited alongside, same era.
X. Chen, D. P. Kingma, T. Salimans, Y. Duan, P. Dhariwal, J. Schulman, I. Sutskever, and P. Abbeel · 2016
Cited alongside, same era.
T. Cooijmans, N. Ballas, C. Laurent, Ç. Gülçehre, and A. Courville · 2016
Cited alongside, same era.
A. Papadopoulos, P. Roy, and F. Pachet · 2016
Later among the works it cites.
Deep feature interpolation for image content changes
P. Upchurch, J. Gardner, K. Bala, R. Pless, N. Snavely, and K. Weinberger · 2016
Later among the works it cites.
On unifying deep generative models
Z. Hu, Z. Yang, R. Salakhutdinov, and E. P. Xing · 2017
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Adversarially regularized autoencoders for generating discrete structures
Junbo, Zhao, Y. Kim, K. Zhang, A. M. Rush, and Y. LeCun · 2017
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Semi-supervised generation with cluster-aware generative models
L. Maaløe, M. Fraccaro, and O. Winther · 2017
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