On Feature Relevance Uncertainty: A Monte Carlo Dropout Sampling Approach

4 August 2020

Papers citing "On Feature Relevance Uncertainty: A Monte Carlo Dropout Sampling Approach"

4 / 4 papers shown

Title
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models Wojciech Samek Thomas Wiegand K. Müller XAI VLM 68 1,189 0 28 Aug 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 192 3,869 0 10 Apr 2017
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 587 15,874 0 12 Nov 2013
How to Explain Individual Classification Decisions D. Baehrens T. Schroeter Stefan Harmeling M. Kawanabe K. Hansen K. Müller FAtt 126 1,103 0 06 Dec 2009