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[1] Julien Cornebise,et al. Weight Uncertainty in Neural Networks , 2015, ArXiv.
[2] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] B. Ripley,et al. Pattern Recognition , 1968, Nature.
[4] Yann LeCun,et al. Regularization of Neural Networks using DropConnect , 2013, ICML.
[5] Prabhat,et al. Scalable Bayesian Optimization Using Deep Neural Networks , 2015, ICML.
[6] Alex Graves,et al. Practical Variational Inference for Neural Networks , 2011, NIPS.
[7] Misha Denil,et al. Predicting Parameters in Deep Learning , 2014 .
[8] Brendan J. Frey,et al. Adaptive dropout for training deep neural networks , 2013, NIPS.
[9] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[10] Ming Yang,et al. DeepFace: Closing the Gap to Human-Level Performance in Face Verification , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[11] Zoubin Ghahramani,et al. Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference , 2015, ArXiv.
[12] Geoffrey E. Hinton,et al. Keeping the neural networks simple by minimizing the description length of the weights , 1993, COLT '93.
[13] Yoshua Bengio,et al. Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation , 2013, ArXiv.
[14] R. Venkatesh Babu,et al. Learning the Architecture of Deep Neural Networks , 2015, ArXiv.
[15] Ryan P. Adams,et al. Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks , 2015, ICML.
[16] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[17] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[18] Ariel D. Procaccia,et al. Variational Dropout and the Local Reparameterization Trick , 2015, NIPS.