Fetching the paper…
Reading the bibliography…
Generative adversarial networks (GANs) are a recently proposed class of generative models in which a generator is trained to optimize a cost function that is being simultaneously learned by a discriminator.
Algorithms for inverse reinforcement learning
A. Ng, S. Russell, et al · 2000
Earlier work this paper cites.
Convex optimization, 2004
S. Boyd and L. Vandenberghe · 2004
Earlier work this paper cites.
A tutorial on energy-based learning
Y. LeCun, S. Chopra, R. Hadsell, M. Ranzato, and F. Huang · 2006
Earlier work this paper cites.
Maximum entropy inverse reinforcement learning
B. Ziebart, A. Maas, J. A. Bagnell, and A. K. Dey · 2008
Earlier work this paper cites.
Modeling purposeful adaptive behavior with the principle of maximum causal entropy
B. Ziebart · 2010
Earlier work this paper cites.
Relative entropy inverse reinforcement learning
A. Boularias, J. Kober, and J. Peters · 2011
Earlier work this paper cites.
The neural autoregressive distribution estimator
H. Larochelle and I. Murray · 2011
Earlier work this paper cites.
A reduction of imitation learning and structured prediction to no-regret online learning
S. Ross, G. Gordon, and A. Bagnell · 2011
Earlier work this paper cites.
Learning objective functions for manipulation
M. Kalakrishnan, P. Pastor, L. Righetti, and S. Schaal · 2013
Earlier work this paper cites.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Cited alongside, same era.
Data generation as sequential decision making
P. Bachman and D. Precup · 2015
Cited alongside, same era.
Scheduled sampling for sequence prediction with recurrent neural networks
S. Bengio, O. Vinyals, N. Jaitly, and N. Shazeer · 2015
Cited alongside, same era.
An actor-critic algorithm for sequence prediction
D. Bahdanau, P. Brakel, K. Xu, A. Goyal, R. Lowe, J. Pineau, A. Courville, and Y. Bengio · 2016
Cited alongside, same era.
Density estimation using real nvp
L. Dinh, J. Sohl-Dickstein, and S. Bengio · 2016
Cited alongside, same era.
Reward augmented maximum likelihood for neural structured prediction
M. Norouzi, S. Bengio, Z. Chen, N. Jaitly, M. Schuster, Y. Wu, and D. Schuurmans · 2016
Closest in time.
f-gan: Training generative neural samplers using variational divergence minimization
S. Nowozin, B. Cseke, and R. Tomioka · 2016
Closest in time.
Wavenet: A generative model for raw audio
A. v. d. Oord, S. Dieleman, H. Zen, K. Simonyan, O. Vinyals, A. Graves, N. Kalchbrenner, A. Senior, and K. Kavukcuoglu · 2016
Closest in time.
Connecting generative adversarial networks and actor-critic methods
D. Pfau and O. Vinyals · 2016
Closest in time.
Sequence level training with recurrent neural networks
M. Ranzato, S. Chopra, M. Auli, and W. Zaremba · 2016
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
C. Finn, S. Levine, and P. Abbeel · 2016
Cited alongside, same era.
Generative adversarial imitation learning
J. Ho and S. Ermon · 2016
Cited alongside, same era.
Model-free imitation learning with policy optimization
J. Ho, J. K. Gupta, and S. Ermon · 2016
Cited alongside, same era.
Deep directed generative models with energy-based probability estimation
T. Kim and Y. Bengio · 2016
Cited alongside, same era.
Pixel recurrent neural networks
A. van den Oord, N. Kalchbrenner, and K. Kavukcuoglu · 2016
Closest in time.
Google’s neural machine translation system: Bridging the gap between human and machine translation
Y. Wu, M. Schuster, Z. Chen, Q. V. Le, M. Norouzi, W. Macherey, M. Krikun, Y. Cao, Q. Gao, K. Macherey, et al · 2016
Closest in time.
Seqgan: Sequence generative adversarial nets with policy gradient
L. Yu, W. Zhang, J. Wang, and Y. Yu · 2016
Closest in time.
Energy-based generative adversarial network
J. Zhao, M. Mathieu, and Y. LeCun · 2016
Closest in time.