A Survey on Uncertainty Toolkits for Deep Learning

2 May 2022

Papers citing "A Survey on Uncertainty Toolkits for Deep Learning"

7 / 7 papers shown

Title
Uncertainty Quantification for Deep Neural Networks: An Empirical Comparison and Usage Guidelines Michael Weiss Paolo Tonella BDL UQCV 17 11 0 14 Dec 2022
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification Youngseog Chung I. Char Han Guo J. Schneider W. Neiswanger 38 70 0 21 Sep 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 196 0 12 Jul 2021
Natural Language Processing Advancements By Deep Learning: A Survey A. Torfi Rouzbeh A. Shirvani Yaser Keneshloo Nader Tavvaf Edward A. Fox AI4CE VLM 83 215 0 02 Mar 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015
MCMC using Hamiltonian dynamics Radford M. Neal 185 3,266 0 09 Jun 2012