Fetching the paper…
Reading the bibliography…
Several interesting generative learning algorithms involve a complex probability distribution over many random variables, involving intractable normalization constants or latent variable normalization.
Herding dynamic weights for partially observed random field models
Welling, M. (2009) · 2000
Earlier work this paper cites.
Annealed importance sampling
Neal, R. M. (2001) · 2001
Earlier work this paper cites.
On the quantitative analysis of deep belief networks
Salakhutdinov, R. and Murray, I. (2008) · 2008
Earlier work this paper cites.
Evaluating probabilities under high-dimensional latent variable models
Murray, I. and Salakhutdinov, R. (2009) · 2009
Earlier work this paper cites.
Deep Boltzmann machines
Salakhutdinov, R. and Hinton, G. E. (2009) · 2009
Earlier work this paper cites.
Theano: a CPU and GPU math expression compiler
Bergstra, J., Breuleux, O., Bastien, F., Lamblin, P., Pascanu, R., Desjardins, G., Turian, J., Warde-Farley, D., and Bengio, Y. (2010) · 2010
Cited alongside, same era.
Unlearning for better mixing
Breuleux, O., Bengio, Y., and Vincent, P. (2010) · 2010
Cited alongside, same era.
Tempered Markov chain Monte Carlo for training of restricted Boltzmann machine
Desjardins, G., Courville, A., Bengio, Y., Vincent, P., and Delalleau, O. (2010) · 2010
Cited alongside, same era.
Theano: new features and speed improvements
Bastien, F., Lamblin, P., Pascanu, R., Bergstra, J., Goodfellow, I. J., Bergeron, A., Bouchard, N., and Bengio, Y. (2012) · 2012
Cited alongside, same era.
A kernel two-sample test
Gretton, A., Borgwardt, K., Rasch, M., Schoelkopf, B., and Smola, A. (2012) · 2012
Cited alongside, same era.
Better mixing via deep representations
Bengio, Y., Mesnil, G., Dauphin, Y., and Rifai, S. (2013a)
Cited in the paper.
Generalized denoising auto-encoders as generative models
Bengio, Y., Yao, L., Alain, G., and Vincent, P. (2013b)
Cited in the paper.
Generalized denoising auto-encoders as generative models
Bengio, Y., Li, Y., Alain, G., and Vincent, P. (2013c)
Cited in the paper.
Generalized denoising auto-encoders as generative models
Bengio, Y., Yao, L., Alain, G., and Vincent, P. (2013d)
Cited in the paper.
A generative process for sampling contractive auto-encoders
Rifai, S., Bengio, Y., Dauphin, Y., and Vincent, P. (2012a)
Cited in the paper.
A generative process for sampling contractive auto-encoders
Rifai, S., Bengio, Y., Dauphin, Y., and Vincent, P. (2012b) · 2012
Later among the works it cites.
Estimating or propagating gradients through stochastic neurons
Bengio, Y. (2013) · 2013
Closest in time.
Enhanced gradient for training restricted boltzmann machines
Cho, K., Raiko, T., and Ilin, A. (2013) · 2013
Closest in time.
Deep generative stochastic networks trainable by backprop
Bengio, Y., Thibodeau-Laufer, E., and Yosinski, J. (2014) · 2014
Closest in time.
Quickly generating representative samples from an RBM-derived process
Breuleux, O., Bengio, Y., and Vincent, P. (2011) · 2073
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…