research
∙
06/07/2023
Dear XAI Community, We Need to Talk! Fundamental Misconceptions in Current XAI Research
Despite progress in the field, significant parts of current XAI research...
share
research
∙
04/06/2023
Efficient SAGE Estimation via Causal Structure Learning
The Shapley Additive Global Importance (SAGE) value is a theoretically a...
research
∙
10/27/2022
Improvement-Focused Causal Recourse (ICR)
Algorithmic recourse recommendations, such as Karimi et al.'s (2021) cau...
research
∙
06/11/2022
Scientific Inference With Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena
Interpretable machine learning (IML) is concerned with the behavior and ...
research
∙
09/03/2021
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process
Scientists and practitioners increasingly rely on machine learning to mo...
research
∙
07/16/2021
A Causal Perspective on Meaningful and Robust Algorithmic Recourse
Algorithmic recourse explanations inform stakeholders on how to act to r...
research
∙
06/15/2021
Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT)
Global model-agnostic feature importance measures either quantify whethe...
research
∙
07/16/2020
Relative Feature Importance
Interpretable Machine Learning (IML) methods are used to gain insight in...
research
∙
07/08/2020
Pitfalls to Avoid when Interpreting Machine Learning Models
Modern requirements for machine learning (ML) models include both high p...
research
∙
06/08/2020
