Characteristics of Monte Carlo Dropout in Wide Neural Networks

10 July 2020

Papers citing "Characteristics of Monte Carlo Dropout in Wide Neural Networks"

7 / 7 papers shown

Title
Gaussian Process Behaviour in Wide Deep Neural Networks A. G. Matthews Mark Rowland Jiri Hron Richard Turner Zoubin Ghahramani BDL 152 559 0 30 Apr 2018
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 131 1,097 0 01 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 283 8,904 0 25 Aug 2017
Concrete Dropout Y. Gal Jiri Hron Alex Kendall BDL UQCV 179 593 0 22 May 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 359 4,718 0 15 Mar 2017
Using the Output Embedding to Improve Language Models Ofir Press Lior Wolf 82 736 0 20 Aug 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 836 9,345 0 06 Jun 2015