Understanding Deep Neural Networks through Input Uncertainties

31 October 2018

Papers citing "Understanding Deep Neural Networks through Input Uncertainties"

4 / 4 papers shown

Title
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models Jayaraman J. Thiagarajan Bindya Venkatesh Rushil Anirudh P. Bremer J. Gaffney G. Anderson B. Spears 18 21 0 05 May 2020
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Values Approximation Marco Ancona Cengiz Öztireli Markus Gross FAtt TDI 30 223 0 26 Mar 2019
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015