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Results: 130
Number of items: 130
  • Open Access
    Auzina, I. A., Yıldız, Ç., Magliacane, S., Bethge, M., & Gavves, E. (2023). Modulated Neural ODEs. 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 (pp. 44572-44594). (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://doi.org/10.52202/075280-1931
  • Open Access
    Zoetmulder, R. (2023). Deep-learning-based image segmentation for uncommon ischemic stroke: From infants to adults. [Thesis, fully internal, Universiteit van Amsterdam].
  • Schirris, Y., Engelaer, M., Panteli, A., Horlings, H. M., Gavves, E., & Teuwen, J. (2022). WeakSTIL: Weak whole-slide image level stromal tumor infiltrating lymphocyte scores are all you need. In J. E. Tomaszewski, A. D. Ward, & R. M. Levenson (Eds.), Medical Imaging 2022: Digital and Computational Pathology: 21-27 March 2022, online Article 120390B (Proceedings of SPIE; Vol. 12039), (Progress in Biomedical Optics and Imaging; Vol. 23, No. 55). SPIE. https://doi.org/10.1117/12.2611528
  • Open Access
    Lippe, P., Cohen, T., & Gavves, E. (2022). Efficient Neural Causal Discovery without Acyclicity Constraints. In The Tenth International Conference on Learning Representations: ICLR 2022 https://openreview.net/forum?id=eYciPrLuUhG
  • Open Access
    Pervez, A., & Gavves, E. (2022). Stability Regularization for Discrete Representation Learning. In The Tenth International Conference on Learning Representations: ICLR 2022 https://openreview.net/forum?id=6tmjoym9LR6
  • Habibian, A., Ben Yahia, H., Abati, D., Gavves, E., & Porikli, F. (2022). Delta Distillation for Efficient Video Processing. In S. Avidan, G. Brostow, M. Cissé, G. M. Farinella, & T. Hassner (Eds.), Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022 : proceedings (Vol. XXXV, pp. 213-229). (Lecture Notes in Computer Science; Vol. 13695). Springer. https://doi.org/10.1007/978-3-031-19833-5_13
  • Schirris, Y., Gavves, E., Nederlof, I., Horlings, H. M., & Teuwen, J. (2022). DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer. Medical Image Analysis, 79, Article 102464. https://doi.org/10.1016/j.media.2022.102464
  • Open Access
    Chen, Y., Fernando, B., Bilen, H., Nießner, M., & Gavves, E. (2022). 3D Equivariant Graph Implicit Functions. In S. Avidan, G. Brostow, M. Cissé, G. M. Farinella, & T. Hassner (Eds.), Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022 : proceedings (Vol. III, pp. 485–502). (Lecture Notes in Computer Science; Vol. 13663). Springer. https://doi.org/10.48550/arXiv.2203.17178, https://doi.org/10.1007/978-3-031-20062-5_28
  • Wang, H., Liu, J., Liu, Y., Maji, S., Sonke, J.-J., & Gavves, E. (2022). Dynamic Transformer for Few-shot Instance Segmentation. In MM '22: proceedings of the 30th ACM International Conference on Multimedia : October 10-14, 2022, Lisboa, Portugal (pp. 2969–2977). The Association for Computing Machinery. https://doi.org/10.1145/3503161.3548227
  • Open Access
    Liu, J., Bao, Y., Xie, G.-S., Xiong, H., Sonke, J.-J., & Gavves, E. (2022). Dynamic Prototype Convolution Network for Few-Shot Semantic Segmentation. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition: New Orleans, Louisiana, 19-24 June 2022 : proceedings (pp. 11543-11552). (CVPR). IEEE Computer Society. https://doi.org/10.48550/arXiv.2204.10638, https://doi.org/10.1109/CVPR52688.2022.01126
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