Variational Inference to Measure Model Uncertainty in Deep Neural Networks

26 February 2019

Papers citing "Variational Inference to Measure Model Uncertainty in Deep Neural Networks"

7 / 7 papers shown

Title
Why Deep Neural Networks for Function Approximation? Shiyu Liang R. Srikant 113 385 0 13 Oct 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 242 4,778 0 04 Jan 2016
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 208 1,510 0 08 Jun 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 252 748 0 06 Jun 2015
Dropout as a Bayesian Approximation: Appendix Y. Gal Zoubin Ghahramani BDL 35 65 0 06 Jun 2015
Caffe: Convolutional Architecture for Fast Feature Embedding Yangqing Jia Evan Shelhamer Jeff Donahue Sergey Karayev Jonathan Long Ross B. Girshick S. Guadarrama Trevor Darrell VLM BDL 3DV 257 14,704 0 20 Jun 2014
Provable Bounds for Learning Some Deep Representations Sanjeev Arora Aditya Bhaskara Rong Ge Tengyu Ma BDL 92 335 0 23 Oct 2013