Instance-Level Explanations for Fraud Detection: A Case Study. - Dennis Collaris; Leo M. Vink; Jarke J. van Wijk (CoRR, 2018)

ExplainExplore: Visual Exploration of Machine Learning Explanations. - Dennis Collaris; Jarke J. van Wijk (PacificVis, 2020)

Machine learning interpretability through contribution-value plots. - Dennis Collaris; Jarke J. van Wijk (VINCI, 2020)

Characterizing Data Scientists' Mental Models of Local Feature Importance. - Dennis Collaris; Hilde J. P. Weerts; Daphne Miedema; Jarke J. van Wijk; Mykola Pechenizkiy (NordiCHI, 2022)

Comparative evaluation of contribution-value plots for machine learning understanding. - Dennis Collaris; Jarke J. van Wijk (J. Vis., 2022)

LEMON: Alternative Sampling for More Faithful Explanation Through Local Surrogate Models. - Dennis Collaris; Pratik Gajane; Joost Jorritsma; Jarke J. van Wijk; Mykola Pechenizkiy (IDA, 2023)

StrategyAtlas: Strategy Analysis for Machine Learning Interpretability. - Dennis Collaris; Jarke J. van Wijk (IEEE Trans. Vis. Comput. Graph., 2023)

RATE-Analytics: Next Generation Predictive Analytics for Data-Driven Banking and Insurance. - Dennis Collaris; Mykola Pechenizkiy; Jarke J. van Wijk (Commit2Data, 2024)

Benefits of Machine Learning Explanations: Improved Learning in an AI-assisted Sequence Prediction Task. - Yu Liang; Dennis Collaris; Martijn C. Willemsen; Jarke J. van Wijk (IUI, 2025)

Cluster-Based Random Forest Visualization and Interpretation. - Max Sondag; Christofer Meinecke; Dennis Collaris; Tatiana von Landesberger; Stef van den Elzen (CoRR, 2025)