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Results: 29
Number of items: 29
  • Open Access
    Kolk, M. Z. H., Ruipérez-Campillo, S., Allaart, C. P., Wilde, A. A. M., Knops, R. E., Narayan, S. M., Tjong, F. V. Y., & DEEP RISK investigators (2024). Multimodal explainable artificial intelligence identifies patients with non-ischaemic cardiomyopathy at risk of lethal ventricular arrhythmias. Scientific Reports, 14, Article 14889. https://doi.org/10.1038/s41598-024-65357-x
  • Open Access
    Marzella, D. F., Crocioni, G., Radusinović, T., Lepikhov, D., Severin, H., Bodor, D. L., Rademaker, D. T., Lin, C., Georgievska, S., Renaud, N., Kessler, A. L., Lopez-Tarifa, P., Buschow, S. I., Bekkers, E., & Xue, L. C. (2024). Geometric deep learning improves generalizability of MHC-bound peptide predictions. Communications biology, 7, Article 1661. https://doi.org/10.1038/s42003-024-07292-1
  • Open Access
    Ranum, O., Wessels, D., Otterspeer, G., Bekkers, E. J., Roelofsen, F., & Andersen, J. I. (2024). The NGT200 Dataset: Geometric Multi-View Isolated Sign Recognition. Proceedings of Machine Learning Research, 251, 286-302. https://proceedings.mlr.press/v251/ranum24a.html
  • Open Access
    Islam, M. M., de Vente, C., Liefers, B., Klaver, C., Bekkers, E. J., & Sánchez, C. I. (2024). Uncertainty-aware retinal layer segmentation in OCT through probabilistic signed distance functions. Proceedings of Machine Learning Research, 250, 672-693. https://doi.org/10.48550/arXiv.2412.04935
  • Open Access
    Moskalev, A. (2024). Representation learning with structured invariance. [Thesis, fully internal, Universiteit van Amsterdam].
  • Kofinas, M., Bekkers, E., Nagaraja, N. S., & Gavves, S. (2023, December 13). Dynamic gravitational field dataset - Latent Field Discovery in Interacting Dynamical Systems with Neural Fields [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10634923
  • Kofinas, M., Bekkers, E., Nagaraja, N. S., & Gavves, S. (2023, December 13). Electrostatic field dataset - Latent Field Discovery in Interacting Dynamical Systems with Neural Fields [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10631646
  • Duits, R., Smets, B. M. N., Wemmenhove, A. J., Portegies, J. W., & Bekkers, E. J. (2023). Recent Geometric Flows in Multi-orientation Image Processing via a Cartan Connection. In K. Chen, C.-B. Schönlieb, X.-C. Tai, & L. Younces (Eds.), Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision (pp. 1525–1583). Springer. https://doi.org/10.1007/978-3-030-98661-2_101, https://doi.org/10.1007/978-3-030-03009-4_101-1
  • Open Access
    Kofinas, M., Bekkers, E. J., Nagaraja, N. S., & Gavves, E. (2023). Latent Field Discovery in Interacting Dynamical Systems with Neural Fields. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), 37th Conference on Neural Information Processing Systems (NeurIPS 2023): 10-16 December 2023, New Orleans, Louisana, USA (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper_files/paper/2023/hash/6521bd47ebaa28228cd6c74cb85afb65-Abstract-Conference.html
  • Open Access
    Knigge, D. M., Romero, D. W., & Bekkers, E. J. (2022). Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups. Proceedings of Machine Learning Research, 162, 11359-11386. https://proceedings.mlr.press/v162/knigge22a.html
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