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

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

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

clone wiki:

git clone git@git.l3s.uni-hannover.de:anand/interpretability.wiki.git
cd interpretability.wiki

install vscode extension yzhang.markdown-all-in-one
install vscode extension goessner.mdmath
go to user settings, search for mdmath and set Delimiters to 'gitlab'
The vscode markdown preview should now render according to the gitlab markdown standard
commit and push changes using git
images can be put into the uploads folder and refered to as ./uploads/image.png