暂无分享,去创建一个
[1] Radford M. Neal. Connectionist Learning of Belief Networks , 1992, Artif. Intell..
[2] Geoffrey E. Hinton,et al. Autoencoders, Minimum Description Length and Helmholtz Free Energy , 1993, NIPS.
[3] Geoffrey E. Hinton,et al. The Helmholtz Machine , 1995, Neural Computation.
[4] Geoffrey E. Hinton,et al. The "wake-sleep" algorithm for unsupervised neural networks. , 1995, Science.
[5] Michael I. Jordan,et al. Mean Field Theory for Sigmoid Belief Networks , 1996, J. Artif. Intell. Res..
[6] Geoffrey E. Hinton,et al. Varieties of Helmholtz Machine , 1996, Neural Networks.
[7] Lex Weaver,et al. The Optimal Reward Baseline for Gradient-Based Reinforcement Learning , 2001, UAI.
[8] Peter L. Bartlett,et al. Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning , 2001, J. Mach. Learn. Res..
[9] Ronald J. Williams,et al. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning , 2004, Machine Learning.
[10] Michael I. Jordan,et al. An Introduction to Variational Methods for Graphical Models , 1999, Machine Learning.
[11] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[12] Ruslan Salakhutdinov,et al. On the quantitative analysis of deep belief networks , 2008, ICML '08.
[13] J. Andrew Bagnell,et al. Differential Sparse Coding , 2008 .
[14] David M. Bradley,et al. Differentiable Sparse Coding , 2008, NIPS.
[15] Geoffrey E. Hinton,et al. Deep Boltzmann Machines , 2009, AISTATS.
[16] Geoffrey E. Hinton,et al. Replicated Softmax: an Undirected Topic Model , 2009, NIPS.
[17] Hugo Larochelle,et al. Efficient Learning of Deep Boltzmann Machines , 2010, AISTATS.
[18] Marc'Aurelio Ranzato,et al. Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition , 2010, ArXiv.
[19] Yann LeCun,et al. Learning Fast Approximations of Sparse Coding , 2010, ICML.
[20] Hugo Larochelle,et al. The Neural Autoregressive Distribution Estimator , 2011, AISTATS.
[21] Michael I. Jordan,et al. Variational Bayesian Inference with Stochastic Search , 2012, ICML.
[22] Hugo Larochelle,et al. A Neural Autoregressive Topic Model , 2012, NIPS.
[23] Ruslan Salakhutdinov,et al. Learning Stochastic Feedforward Neural Networks , 2013, NIPS.
[24] Daan Wierstra,et al. Stochastic Backpropagation and Approximate Inference in Deep Generative Models , 2014, ICML.
[25] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[26] Daan Wierstra,et al. Deep AutoRegressive Networks , 2013, ICML.
[27] Sean Gerrish,et al. Black Box Variational Inference , 2013, AISTATS.
[28] Daan Wierstra,et al. Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models , 2014, ArXiv.