Explaining Models by Propagating Shapley Values of Local Components

Explaining Models by Propagating Shapley Values of Local Components

27 November 2019

Scott M. Lundberg

Papers citing "Explaining Models by Propagating Shapley Values of Local Components"

16 / 16 papers shown

Title
Accurate Explanation Model for Image Classifiers using Class Association Embedding Ruitao Xie Jingbang Chen Limai Jiang Rui Xiao Yi-Lun Pan Yunpeng Cai 218 4 0 31 Dec 2024
Explainable AI for Autism Diagnosis: Identifying Critical Brain Regions Using fMRI Data Suryansh Vidya Kush Gupta Amir Aly Andy Wills Emmanuel Ifeachor Rohit Shankar 79 1 0 19 Sep 2024
T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients Evandro S. Ortigossa Fábio F. Dias Brian Barr Claudio T. Silva L. G. Nonato FAtt 101 3 0 25 Apr 2024
Feature relevance quantification in explainable AI: A causal problem Dominik Janzing Lenon Minorics Patrick Blobaum FAtt CML 60 280 0 29 Oct 2019
Generalized Integrated Gradients: A practical method for explaining diverse ensembles John Merrill Geoff Ward S. Kamkar Jay Budzik Douglas C. Merrill 34 15 0 04 Sep 2019
The many Shapley values for model explanation Mukund Sundararajan A. Najmi TDI FAtt 58 632 0 22 Aug 2019
Improving performance of deep learning models with axiomatic attribution priors and expected gradients G. Erion Joseph D. Janizek Pascal Sturmfels Scott M. Lundberg Su-In Lee OOD BDL FAtt 54 81 0 25 Jun 2019
Explainable AI for Trees: From Local Explanations to Global Understanding Scott M. Lundberg G. Erion Hugh Chen A. DeGrave J. Prutkin B. Nair R. Katz J. Himmelfarb N. Bansal Su-In Lee FAtt 86 290 0 11 May 2019
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Values Approximation Marco Ancona Cengiz Öztireli Markus Gross FAtt TDI 70 225 0 26 Mar 2019
What do we need to build explainable AI systems for the medical domain? Andreas Holzinger Chris Biemann C. Pattichis D. Kell 66 689 0 28 Dec 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,864 0 22 May 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 194 3,869 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 177 5,986 0 04 Mar 2017
European Union regulations on algorithmic decision-making and a "right to explanation" B. Goodman Seth Flaxman FaML AILaw 63 1,899 0 28 Jun 2016
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 307 7,292 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 589 15,876 0 12 Nov 2013