A Bayesian finite-element trained machine learning approach for predicting post-burn contraction. - Ginger Egberts; Marianne Schaaphok; Fred J. Vermolen; Paul van Zuijlen (Neural Comput. Appl., 2022)

Random Sample as a Pre-pilot Evaluation of Benefits and Risks for AI in Public Sector. - Steven Vethman; Marianne Schaaphok; Marissa Hoekstra; Cor J. Veenman (ECAI Workshops (2), 2023)

ReSGrAL: Fairness-Sensitive Active Learning. - Nina M. van Liebergen; Marianne Schaaphok; Giovanni Sileno (AIEB@ECAI, 2024)

Affordance Perception by a Knowledge-Guided Vision-Language Model with Efficient Error Correction. - Gertjan J. Burghouts; Marianne Schaaphok; Michael van Bekkum; Wouter Meijer; Fieke Hillerström; Jelle van Mil (ICPRAI (2), 2024)