Survey of explainable machine learning with visual and granular methods beyond quasi-explanations

21 September 2020

Papers citing "Survey of explainable machine learning with visual and granular methods beyond quasi-explanations"

12 / 12 papers shown

Title
Questioning the AI: Informing Design Practices for Explainable AI User Experiences Q. V. Liao D. Gruen Sarah Miller 107 715 0 08 Jan 2020
Conditional Parallel Coordinates D. Weidele 33 17 0 18 Jun 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 84 1,009 0 26 Feb 2019
On the Units of GANs (Extended Abstract) David Bau Jun-Yan Zhu Hendrik Strobelt Bolei Zhou J. Tenenbaum William T. Freeman Antonio Torralba 48 61 0 29 Jan 2019
RuleMatrix: Visualizing and Understanding Classifiers with Rules Yao Ming Huamin Qu E. Bertini FAtt 59 215 0 17 Jul 2018
Visual Analytics for Explainable Deep Learning Jaegul Choo Shixia Liu HAI XAI 55 236 0 07 Apr 2018
Interpreting CNNs via Decision Trees Quanshi Zhang Yu Yang Ying Nian Wu Song-Chun Zhu FAtt 67 323 0 01 Feb 2018
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models Wojciech Samek Thomas Wiegand K. Müller XAI VLM 68 1,188 0 28 Aug 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 276 2,257 0 24 Jun 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 236 4,249 0 22 Jun 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 310 4,623 0 10 Nov 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 154 3,685 0 10 Jun 2016