  | Vandeghen, R., Thoker, F. M., Ghanem, B., & Van Droogenbroeck, M. (2026). TrackMAE: Video Representation Learning via Track Mask and Predict. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/340035. |
 | Held, J., Son, S., Vandeghen, R., Rebain, D., Gadelha, M., Zhou, Y., Cioppa, A., Lin, M. C., Van Droogenbroeck, M., & Tagliasacchi, A. (2025). MeshSplatting: Differentiable Rendering with Opaque Meshes. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/338445. |
 | Held, J., Vandeghen, R., Son, S., Rebain, D., Gadelha, M., Zhou, Y., Lin, M. C., Van Droogenbroeck, M., & Tagliasacchi, A. (2025). Triangle Splatting+: Differentiable Rendering with Opaque Triangles. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/338444. |
 | Held, J.* , Vandeghen, R.* , Hamdi, A.* , Deliège, A., Cioppa, A., Giancola, S., Vedaldi, A., Ghanem, B., & Van Droogenbroeck, M. (13 August 2025). 3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes [Paper presentation]. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), nashville, United States. doi:10.1109/CVPR52734.2025.01990  Peer reviewed* These authors have contributed equally to this work. |
 | Schmitz, V., Vandeghen, R., Erpicum, S., Pirotton, M., Archambeau, P., & Dewals, B. (2025). How Do decision-tree-based Machine Learning Techniques Compare To Hybrid Approaches for Predicting Fluvial Dike Breach Discharge? Water Resources Management. doi:10.1007/s11269-025-04318-z Peer Reviewed verified by ORBi |
 | Held, J.* , Vandeghen, R.* , Deliège, A., Hamdi, A., Giancola, S., Cioppa, A., Vedaldi, A., Ghanem, B., Tagliasacchi, A., & Van Droogenbroeck, M. (2025). Triangle Splatting for Real-Time Radiance Field Rendering. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/334146. * These authors have contributed equally to this work. |
 | Schmitz, V., Pierard, S., Vandeghen, R., Erpicum, S., Pirotton, M., Archambeau, P., & Dewals, B. (2025). Comparison of machine learning techniques and empirical formulas for the prediction of the discharge through a fluvial dike breach [Paper presentation]. 41st IAHR World Congress, Singapore. Peer reviewed |
 | Halin, A.* , Pierard, S.* , Vandeghen, R., Gérin, B., Zanella, M., Colot, M., Held, J., Cioppa, A., Jean, E., Bontempi, G., Mahmoudi, S., Macq, B., & Van Droogenbroeck, M. (09 December 2024). Physically Interpretable Probabilistic Domain Characterization [Paper presentation]. First International Workshop on AI-based All-Weather Surveillance System (AWSS), Hanoï, Vietnam. Peer reviewed* These authors have contributed equally to this work. |
 | Eymaël, A.* , Vandeghen, R.* , Cioppa, A., Giancola, S., Ghanem, B., & Van Droogenbroeck, M. (2024). Efficient Image Pre-Training with Siamese Cropped Masked Autoencoders. In European Conference on Computer Vision (pp. 348–366). Springer. doi:10.1007/978-3-031-73337-6_20 Peer reviewed* These authors have contributed equally to this work. |
 | Halin, A.* , Pierard, S.* , Vandeghen, R., Gérin, B., Zanella, M., Colot, M., Held, J., Cioppa, A., Jean, E., Bontempi, G., Mahmoudi, S., Macq, B., & Van Droogenbroeck, M. (2024). Physically Interpretable Probabilistic Domain Characterization. In Proceedings of ACCV 2024. The Computer Vision Foundation (CVF). doi:10.1007/978-981-96-2641-0_2 Peer reviewed* These authors have contributed equally to this work. |
 | Vandeghen, R., Louppe, G., & Van Droogenbroeck, M. (October 2023). Adaptive Self-Training for Object Detection [Poster presentation]. IEEE/CVF International Conference on Computer Vision Workshops (ICCV Workshops), Paris, France. doi:10.1109/ICCVW60793.2023.00098 Peer reviewed |
 | Pierard, S., Cioppa, A., Halin, A., Vandeghen, R., Maxime Zanella, Benoît Macq, Saïd Mahmoudi, & Van Droogenbroeck, M. (30 March 2023). Pushing AI out of the lab with on-the-fly mixture domain adaptation [Paper presentation]. The European AI week, Brussels, Belgium. |
 | Pierard, S., Cioppa, A., Halin, A., Vandeghen, R., Maxime Zanella, Benoît Macq, Saïd Mahmoudi, & Van Droogenbroeck, M. (2023). Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance. In Proceedings of IEEE/CVF Winter Conference on Applications of Computer Vision (WACVW) (pp. 22-31). Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/wacvw58289.2023.00007 Peer reviewed |
 | Vandeghen, R.* , Cioppa, A.* , & Van Droogenbroeck, M. (2022). Semi-Supervised Training to Improve Player and Ball Detection in Soccer. In IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. 3480-3489). Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/cvprw56347.2022.00392 Peer reviewed* These authors have contributed equally to this work. |
 | Vandeghen, R.* , Cioppa, A.* , & Van Droogenbroeck, M. (03 May 2022). Semi-Supervised Training to Improve Detection for Satellite Images [Poster presentation]. AI4Copernicus: Earth Observation and Artificial Intelligence for a Safer World, Bruxelles, Belgium. * These authors have contributed equally to this work. |
 | Van Droogenbroeck, M., Wagner, J.-M., Pierlot, V., Latour, P., & Vandeghen, R. (2021). Analysis and Design of Telecommunications Systems: Manual of Exercises. (ULiège - Université de Liège, ELEN0017-1 Analysis and Design of Telecommunications Systems). |
 | Van Droogenbroeck, M., Latour, P., Wagner, J.-M., Pierlot, V., & Vandeghen, R. (2020). Principes des télécommunications analogiques et numériques: manuel des répétitions. (ULiège - Université de Liège, Belgium, ELEN0008-1 Principes des télécommunications analogiques et numériques). |
