暂无分享,去创建一个
Qiao Li | Chun Jason Xue | Antoni B. Chan | Yufei Cui | Wuguannan Yao | Qiao Li | C. Xue | Yufei Cui | Wuguannan Yao
[1] Gabriel Peyré,et al. Computational Optimal Transport , 2018, Found. Trends Mach. Learn..
[2] C. Villani. Optimal Transport: Old and New , 2008 .
[3] Mark J. F. Gales,et al. Predictive Uncertainty Estimation via Prior Networks , 2018, NeurIPS.
[4] James Hensman,et al. Scalable Variational Gaussian Process Classification , 2014, AISTATS.
[5] Anke Schmeink,et al. Variational Network Quantization , 2018, ICLR.
[6] Wei Pan,et al. Towards Accurate Binary Convolutional Neural Network , 2017, NIPS.
[7] Bernhard Schölkopf,et al. Wasserstein Auto-Encoders , 2017, ICLR.
[8] James G. Scott,et al. Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables , 2012, 1205.0310.
[9] Lorenzo Porzi,et al. Dropout distillation , 2016, ICML.
[10] James Hensman,et al. MCMC for Variationally Sparse Gaussian Processes , 2015, NIPS.
[11] Shakir Mohamed,et al. Implicit Reparameterization Gradients , 2018, NeurIPS.
[12] Fei-Fei Li,et al. ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[13] Zoubin Ghahramani,et al. Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning , 2015, ICML.
[14] Kevin Gimpel,et al. A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks , 2016, ICLR.
[15] Ran El-Yaniv,et al. Binarized Neural Networks , 2016, ArXiv.
[16] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[17] Wolfram Burgard,et al. The limits and potentials of deep learning for robotics , 2018, Int. J. Robotics Res..
[18] Song Han,et al. Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding , 2015, ICLR.
[19] Alex Kendall,et al. What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? , 2017, NIPS.
[20] Masashi Sugiyama,et al. Bayesian Dark Knowledge , 2015 .
[21] Xiang Wei,et al. Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect , 2018, ICLR.
[22] Ran El-Yaniv,et al. Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations , 2016, J. Mach. Learn. Res..
[23] Yee Whye Teh,et al. Bayesian Learning via Stochastic Gradient Langevin Dynamics , 2011, ICML.
[24] M. C. Jones,et al. The Statistical Analysis of Compositional Data , 1986 .
[25] Vivek Rathod,et al. Bayesian dark knowledge , 2015, NIPS.
[26] Zoubin Ghahramani,et al. Compact approximations to Bayesian predictive distributions , 2005, ICML.