Tractogram Filtering of Anatomically Non-plausible Fibers with Geometric Deep Learning. - Pietro Astolfi; Ruben S. Verhagen; Laurent Petit; Emanuele Olivetti; Jonathan Masci; Davide Boscaini; Paolo Avesani (MICCAI (7), 2020)

A Two-Dimensional Explanation Framework to Classify AI as Incomprehensible, Interpretable, or Understandable. - Ruben S. Verhagen; Mark A. Neerincx; Myrthe L. Tielman (EXTRAAMAS@AAMAS, 2021)

Exploring Effectiveness of Explanations for Appropriate Trust: Lessons from Cognitive Psychology. - Ruben S. Verhagen; Siddharth Mehrotra; Mark A. Neerincx; Catholijn M. Jonker; Myrthe L. Tielman (CoRR, 2022)

The influence of interdependence and a transparent or explainable communication style on human-robot teamwork. - Ruben S. Verhagen; Mark A. Neerincx; Myrthe L. Tielman (Frontiers Robotics AI, 2022)

Personalized Agent Explanations for Human-Agent Teamwork: Adapting Explanations to User Trust, Workload, and Performance. - Ruben S. Verhagen; Mark A. Neerincx; Can Parlar; Marin Vogel; Myrthe L. Tielman (AAMAS, 2023)

Supervised tractogram filtering using Geometric Deep Learning. - Pietro Astolfi; Ruben S. Verhagen; Laurent Petit; Emanuele Olivetti; Silvio Sarubbo; Jonathan Masci; Davide Boscaini; Paolo Avesani (Medical Image Anal., 2023)

The Influence of Interdependence on Trust Calibration in Human-Machine Teams. - Ruben S. Verhagen; Alexandra Marcu; Mark A. Neerincx; Myrthe L. Tielman (HHAI, 2024)

Meaningful human control and variable autonomy in human-robot teams for firefighting. - Ruben S. Verhagen; Mark A. Neerincx; Myrthe L. Tielman (Frontiers Robotics AI, 2024)

Agent Allocation of Moral Decisions in Human-Agent Teams: Raise Human Involvement and Explain Potential Consequences. - Ruben S. Verhagen; Mark A. Neerincx; Myrthe L. Tielman (FAccT, 2025)