| 2026 | AIME | AnchorNet: A Clinically Grounded Causal Model for Personalized Medicine. | Louk van Remmerden, Mark Hoogendoorn, Vincent Franois-Lavet, Shujian Yu, Hein van Hout |
| 2025 | AIME | Generalizability of AI Survival Models in the Context of Preterm Birth Prediction. | Anne M. Fischer, Isabelle Dehaene, Mark Hoogendoorn |
| 2025 | AIME | Personalizing mHealth Apps with Offline Reinforcement Learning: A Case Study on Mental Health App Adherence. | Rutger van der Linden, Khadicha Amarti, Marketa Ciharova, Annet Kleiboer, Heleen Riper, Aneta Lisowska, Mark Hoogendoorn |
| 2025 | ICLR | Start Smart: Leveraging Gradients For Enhancing Mask-based XAI Methods. | Buelent Uendes, Shujian Yu, Mark Hoogendoorn |
| 2023 | ECAI | Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study. | Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn |
| 2023 | ICLR | Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN. | David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke |
| 2023 | ICMLA | Channel-Adaptive Early Exiting Using Reinforcement Learning for Multivariate Time Series Classification. | Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal |
| 2022 | DCOSS | Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveS. | Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal |
| 2022 | ICLR | FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes. | David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan van Gemert |
| 2022 | ICLR | CKConv: Continuous Kernel Convolution For Sequential Data. | David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn |
| 2022 | ICMLA | An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different Dimensions. | Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn, Henri E. Bal |
| 2022 | IJCAI | Reinforcement Learning with Option Machines. | Floris den Hengst, Vincent Franois-Lavet, Mark Hoogendoorn, Frank van Harmelen |
| 2020 | ICLR | Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring in Data. | David W. Romero, Mark Hoogendoorn |
| 2020 | ICML | Attentive Group Equivariant Convolutional Networks. | David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn |
| 2019 | BPM | Trace Clustering on Very Large Event Data in Healthcare Using Frequent Sequence Patterns. | Xixi Lu, Seyed Amin Tabatabaei, Mark Hoogendoorn, Hajo A. Reijers |
| 2019 | HealthCom | Identifying Patient Groups based on Frequent Patterns of Patient Samples. | Seyed Amin Tabatabaei, Xixi Lu, Mark Hoogendoorn, Hajo A. Reijers |
| 2018 | PRIMA | Using Generative Adversarial Networks to Develop a Realistic Human Behavior Simulator. | Ali el Hassouni, Mark Hoogendoorn, Vesa Muhonen |
| 2018 | PRIMA | Personalization of Health Interventions Using Cluster-Based Reinforcement Learning. | Ali el Hassouni, Mark Hoogendoorn, Martijn van Otterlo, Eduardo Barbaro |
| 2018 | PRIMA | Narrowing Reinforcement Learning: Overcoming the Cold Start Problem for Personalized Health Interventions. | Seyed Amin Tabatabaei, Mark Hoogendoorn, Aart van Halteren |
| 2015 | AIME | An Evaluation Framework for the Comparison of Fine-Grained Predictive Models in Health Care. | Ward R. J. van Breda, Mark Hoogendoorn, A. E. Eiben, Matthias Berking |
| 2015 | AIME | On the Advantage of Using Dedicated Data Mining Techniques to Predict Colorectal Cancer. | Reinier Kop, Mark Hoogendoorn, Leon M. G. Moons, Mattijs E. Numans, Annette ten Teije |
| 2014 | GECCO | Generic parameter control with reinforcement learning. | Giorgos Karafotias, goston E. Eiben, Mark Hoogendoorn |
| 2013 | CEC | Why parameter control mechanisms should be benchmarked against random variation. | Giorgos Karafotias, Mark Hoogendoorn, A. E. Eiben |
| 2013 | GECCO | Parameter control: strategy or luck? | Giorgos Karafotias, Mark Hoogendoorn, A. E. Eiben |
| 2012 | PPSN | On-Line Evolution of Controllers for Aggregating Swarm Robots in Changing Environments. | Berend Weel, Mark Hoogendoorn, A. E. Eiben |
| 2011 | HCI | Performance Measures to Enable Agent-Based Support in Demanding Circumstances. | Fiemke Both, Mark Hoogendoorn, Rianne van Lambalgen, Rogier Oorburg, Michael de Vos |
| 2011 | ICONIP | Utilization of a Virtual Patient Model to Enable Tailored Therapy for Depressed Patients. | Fiemke Both, Mark Hoogendoorn |
| 2011 | IJCAI | Modeling Situation Awareness in Human-Like Agents Using Mental Models. | Mark Hoogendoorn, Rianne van Lambalgen, Jan Treur |
| 2011 | PRIMA | Learning Belief Connections in a Model for Situation Awareness. | Maria L. Gini, Mark Hoogendoorn, Rianne van Lambalgen |
| 2011 | PRIMA | An Integrated Agent Model Addressing Situation Awareness and Functional State in Decision Making. | Mark Hoogendoorn, Rianne van Lambalgen, Jan Treur |
| 2010 | ICCCI | A Three-Dimensional Abstraction Framework to Compare Multi-Agent System Models. | Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur |
| 2010 | ICONIP | Computational Modeling and Analysis of the Role of Physical Activity in Mood Regulation and Depression. | Fiemke Both, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur |
| 2010 | ICONIP | Modelling the Interplay of Emotions, Beliefs and Intentions within Collective Decision Making Based on Insights from Social Neuroscience. | Mark Hoogendoorn, Jan Treur, C. Natalie van der Wal, Arlette van Wissen |
| 2010 | PAAMS | A Model-Based Ambient Agent Providing Support in Handling Desire and Temptation. | Mark Hoogendoorn, Zulfiqar Ali Memon, Jan Treur, Muhammad Umair |
| 2009 | ECMS | Avoidance of Norm Violation in Multi-Agent Organizations. | Charlotte Gerritsen, Mark Hoogendoorn |
| 2009 | HCI | A Generic Personal Assistant Agent Model for Support in Demanding Tasks. | Tibor Bosse, Rob Duell, Mark Hoogendoorn, Michel C. A. Klein, Rianne van Lambalgen, Andy van der Mee, Rogier Oorburg, Alexei Sharpanskykh, Jan Treur, Michael de Vos |
| 2009 | PRIMA | Adaptation and Validation of an Agent Model of Functional State and Performance for Individuals. | Fiemke Both, Mark Hoogendoorn, S. Waqar Jaffry, Rianne van Lambalgen, Rogier Oorburg, Alexei Sharpanskykh, Jan Treur, Michael de Vos |
| 2008 | ECAI | Agent-Based and Population-Based Simulation of Displacement of Crime (extended abstract). | Tibor Bosse, Charlotte Gerritsen, Mark Hoogendoorn, S. Waqar Jaffry, Jan Treur |
| 2008 | ECAI | Modeling the Dynamics of Mood and Depression. | Fiemke Both, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur |
| 2008 | ECAI | Agents Preferences in Decentralized Task Allocation. | Mark Hoogendoorn, Maria L. Gini |
| 2008 | UIC | A Component-Based Ambient Agent Model for Assessment of Driving Behaviour. | Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur |
| 2007 | IJCAI | Adaptation of Organizational Models for Multi-Agent Systems Based on Max Flow Networks. | Mark Hoogendoorn |
| 2006 | Coordination | Automated Evaluation of Coordination Approaches. | Tibor Bosse, Mark Hoogendoorn, Jan Treur |
| 2004 | SGAI | Formal Analysis of Empirical Traces in Incident Management. | Mark Hoogendoorn, Catholijn M. Jonker, Savas Konur, Peter-Paul van Maanen, Viara Popova, Alexei Sharpanskykh, Jan Treur, Lai Xu, Pinar Yolum |