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Resources

Tutorials

Title Venue Authors slides
Interpretable ML: The fuss, the concrete and the questions ICML 2017 Kim and Doshi-Velez link
Tutorial on XKDD XKDD Workshop ECML 2018 Monreale et al. link
Explainable AI in Industry KDD 2019 Geyik et al., LinkedIn link
On Explainable AI:From Theory to Motivation, Applications and Limitations AAAI 2019 many link

Overviews, Surveys, Reviews

Title Author link
The Mythos of Model Interpretability Lipton arxiv
Towards a Rigorous Science of Interpretable Machine Learning Doshi-Velez and Kim arxiv
A Survey of Methods for Explaining Black Box Models Guidotti et al. arxiv
Interpretability of Machine Learning Models and Representations: an Introduction Adrien Bibal and Benoît Frénay pdf

Books

Title Author link
Interpretable ML: A Guide for Making Black Box Models Explainable. Molnar link
Limitations of Interpretable Machine Learning Methods LMU seminar link