"Why Should You Trust My Explanation?" Understanding Uncertainty in LIME Explanations

29 April 2019

Papers citing ""Why Should You Trust My Explanation?" Understanding Uncertainty in LIME Explanations"

7 / 7 papers shown

Title
Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation S. Tan R. Caruana Giles Hooker Yin Lou MLAU 101 185 0 17 Oct 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 188 3,869 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 175 5,986 0 04 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 382 3,776 0 28 Feb 2017
The Mythos of Model Interpretability Zachary Chase Lipton FaML 172 3,690 0 10 Jun 2016
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Shcherbina A. Kundaje FAtt 80 788 0 05 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.1K 16,931 0 16 Feb 2016