CXPlain: Causal Explanations for Model Interpretation under Uncertainty

27 October 2019

Papers citing "CXPlain: Causal Explanations for Model Interpretation under Uncertainty"

8 / 108 papers shown

Title
Adversarial Infidelity Learning for Model Interpretation Jian Liang Bing Bai Yuren Cao Kun Bai Fei Wang AAML 103 18 0 09 Jun 2020
Clinical Predictive Models for COVID-19: Systematic Study Patrick Schwab August DuMont Schütte Benedikt Dietz Stefan Bauer OOD ELM 88 35 0 17 May 2020
An interpretable neural network model through piecewise linear approximation Mengzhuo Guo Qingpeng Zhang Xiuwu Liao D. Zeng MILM FAtt 51 8 0 20 Jan 2020
A Deep Learning Approach to Diagnosing Multiple Sclerosis from Smartphone Data Patrick Schwab W. Karlen 68 26 0 02 Jan 2020
Contextual Prediction Difference Analysis for Explaining Individual Image Classifications Jindong Gu Volker Tresp FAtt 51 8 0 21 Oct 2019
Learning Decision Trees Recurrently Through Communication Stephan Alaniz Diego Marcos Bernt Schiele Zeynep Akata 58 16 0 05 Feb 2019
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves Patrick Schwab Lorenz Linhardt Stefan Bauer J. M. Buhmann W. Karlen CML OOD 101 135 0 03 Feb 2019
MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis Rushil Anirudh Jayaraman J. Thiagarajan R. Sridhar T. Bremer FAtt AAML 72 12 0 15 Nov 2017