Scalable Natural Gradient Langevin Dynamics in Practice

7 June 2018

Papers citing "Scalable Natural Gradient Langevin Dynamics in Practice"

7 / 7 papers shown

Title
Stochastic Gradient Descent as Approximate Bayesian Inference Stephan Mandt Matthew D. Hoffman David M. Blei BDL 59 599 0 13 Apr 2017
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos Max Welling BDL 62 257 0 15 Mar 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 852 9,346 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 192 1,892 0 20 May 2015
Optimizing Neural Networks with Kronecker-factored Approximate Curvature James Martens Roger C. Grosse ODL 104 1,023 0 19 Mar 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 142 945 0 18 Feb 2015
(Non-) asymptotic properties of Stochastic Gradient Langevin Dynamics Sebastian J. Vollmer K. Zygalakis and Yee Whye Teh 87 49 0 02 Jan 2015