4 citations · 4 across the 1 of their papers we have counts for
3 papers
cs.LG2020★ 4 cited
An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks
Udo Schlegel, Daniela Oelke, Daniel A. Keim +1
Decision explanations of machine learning black-box models are often generated by applying Explainable AI (XAI) techniques. However, many proposed XAI methods produce unverified ou…
cs.LG2019
Towards a Rigorous Evaluation of XAI Methods on Time Series
Udo Schlegel, Hiba Arnout, Mennatallah El-Assady +2
Explainable Artificial Intelligence (XAI) methods are typically deployed to explain and debug black-box machine learning models. However, most proposed XAI methods are black-boxes…
cs.LG2019
Understanding Bias in Machine Learning
Jindong Gu, Daniela Oelke
Bias is known to be an impediment to fair decisions in many domains such as human resources, the public sector, health care etc. Recently, hope has been expressed that the use of m…