Interpretable AI

  1. Interpretable Machine Learning – A Guide for Making Black Box Models Explainable – Christoph Molnar – Link
  2. Interpretable AI – Building explainable machine learning systems, Ajay Thampi – Link

Papers

  1. Multi-Objective Counterfactual Explanations by Susanne Dandl, Christoph Molnar, Martin Binder, Bernd Bischl – Link
  2. Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers by Divyat Mahajan, Chenhao Tan, Amit Sharma – Link
  3. Counterfactual Explanations for Machine Learning: A Review by Sahil Verma, John Dickerson, Keegan Hines – Link