XAI for Graphs: Explaining Graph Neural Network Predictions by Identifying Relevant Walks. - Thomas Schnake; Oliver Eberle; Jonas Lederer; Shinichi Nakajima; Kristof T. Schütt; Klaus-Robert Müller; Grégoire Montavon (CoRR, 2020)

Toward Explainable AI for Regression Models. - Simon Letzgus; Patrick Wagner 002; Jonas Lederer; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (CoRR, 2021)

Automatic Identification of Chemical Moieties. - Jonas Lederer; Michael Gastegger; Kristof T. Schütt; Michael Kampffmeyer; Klaus-Robert Müller; Oliver T. Unke (CoRR, 2022)

Higher-Order Explanations of Graph Neural Networks via Relevant Walks. - Thomas Schnake; Oliver Eberle; Jonas Lederer; Shinichi Nakajima; Kristof T. Schütt; Klaus-Robert Müller; Grégoire Montavon (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Toward Explainable Artificial Intelligence for Regression Models: A methodological perspective. - Simon Letzgus; Patrick Wagner 002; Jonas Lederer; Wojciech Samek; Klaus-Robert Müller; Grégoire Montavon (IEEE Signal Process. Mag., 2022)

Towards symbolic XAI - explanation through human understandable logical relationships between features. - Thomas Schnake; Farnoush Rezaei Jafari; Jonas Lederer; Ping Xiong 002; Shinichi Nakajima; Stefan Gugler; Grégoire Montavon; Klaus-Robert Müller (Inf. Fusion, 2025)