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Results: 114
Number of items: 114
  • Open Access
    Konstantakos, S., Cani, J., Mademlis, I., Chalkiadaki, D. I., Asano, Y. M., Gavves, E., & Papadopoulos, G. T. (2025). Self-supervised visual learning in the low-data regime: A comparative evaluation. Neurocomputing, 620, Article 129199. https://doi.org/10.1016/j.neucom.2024.129199
  • Open Access
    Sträter, L. P. J., Salehidehnavi, S., Gavves, E., Snoek, C. G. M., & Asano, Y. M. (2025). GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features. In A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler, & G. Varol (Eds.), Computer Vision – ECCV 2024: 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part XXXVII (Vol. XXXVII, pp. 448-465). (Lecture Notes in Computer Science; Vol. 15059). Springer. https://doi.org/10.1007/978-3-031-72913-3_25
  • Open Access
    Karageorgiou, D., Papadopoulos, S., Kompatsiaris, I., & Gavves, E. (2025). Any-Resolution AI-Generated Image Detection by Spectral Learning. In 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition : CVPR 2025: Nashville, Tennessee, USA, 11-15 June 2025 : proceedings (pp. 18706-18717). IEEE Computer Society. https://doi.org/10.48550/arXiv.2411.19417, https://doi.org/10.1109/CVPR52734.2025.01743
  • Kofinas, M., Knyazev, B., Zhang, Y., Chen, Y., Burghouts, G. J., Gavves, S., Snoek, C. G., & Zhang, D. (2024, May 8). CNN Wild Park - Graph Neural Networks for Learning Equivariant Representations of Neural Networks [Data set]. Zenodo. https://doi.org/10.5281/zenodo.12797219
  • Open Access
    Egorov, E., Valperga, R., & Gavves, E. (2024). Ai-sampler: Adversarial Learning of Markov kernels with involutive maps. Proceedings of Machine Learning Research, 235, 12304-12317. https://proceedings.mlr.press/v235/egorov24a.html
  • Open Access
    Wang, H., Yan, C., Chen, K., Jiang, X., Tang, X., Hu, Y., Kang, G., Xie, W., & Gavves, E. (2024). OV-VIS: Open-Vocabulary Video Instance Segmentation. International Journal of Computer Vision, 132(11), 5048-5065. https://doi.org/10.1007/s11263-024-02076-w
  • Open Access
    Gabel, A., Quax, R., & Gavves, E. (2024). Data-driven Lie point symmetry detection for continuous dynamical systems. Machine Learning: Science and Technology, 5(1), Article 015037. https://doi.org/10.1088/2632-2153/ad2629
  • Open Access
    Papa, S., Valperga, R., Knigge, D., Kofinas, M., Lippe, P., Sonke, J.-J., & Gavves, E. (2024). How to Train Neural Field Representations: A Comprehensive Study and Benchmark. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition: CVPR 2024 : Seattle, Washington, USA, 16-22 June 2024 : proceedings (pp. 22616-22625). IEEE Computer Society. https://doi.org/10.48550/arXiv.2312.10531, https://doi.org/10.1109/CVPR52733.2024.02134
  • Open Access
    Liu, Y., Magliacane, S., Kofinas, M., & Gavves, E. (2024). Amortized Equation Discovery in Hybrid Dynamical Systems. Proceedings of Machine Learning Research, 235, 31645-31668. https://proceedings.mlr.press/v235/liu24at.html
  • Open Access
    Bereska, J. I., Bereska, L. F., Gavves, E., Gerhards, M. F., Klaase, J. M., Pancreatobiliary and Hepatic Artificial Intelligence Research (PHAIR) consortium, & Dutch Colorectal Cancer Group Liver Expert Panel (2024). Development and external evaluation of a self-learning auto-segmentation model for Colorectal Cancer Liver Metastases Assessment (COALA). Insights into Imaging, 15, Article 279. https://doi.org/10.1186/s13244-024-01820-7
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