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Results: 302
Number of items: 302
  • 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
    Zhang, Y. (2024). Multimodal learning under visually challenging conditions. [Thesis, fully internal, Universiteitsbibliotheek].
  • Open Access
    Ambekar, S., Xiao, Z., Shen, J., Zhen, X., & Snoek, C. G. M. (2024). Probabilistic Test-Time Generalization by Variational Neighbor-Labeling. Proceedings of Machine Learning Research, 274, 832-851. https://proceedings.mlr.press/v274/ambekar25a.html
  • Open Access
    Xiao, Z., Shen, J., Derakhshani, M. M., Liao, S., & Snoek, C. G. M. (2024). Any-Shift Prompting for Generalization over Distributions. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition: CVPR 2024 : Seattle, Washington, USA, 16-22 June 2024 : proceedings (pp. 13849-13860). IEEE Computer Society. https://doi.org/10.48550/arXiv.2402.10099, https://doi.org/10.1109/CVPR52733.2024.01314
  • Open Access
    Dorkenwald, M., Barazani, N., Snoek, C. G. M., & Asano, Y. M. (2024). PIN: Positional Insert Unlocks Object Localisation Abilities in VLMs. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition: CVPR 2024 : Seattle, Washington, USA, 16-22 June 2024 : proceedings (pp. 13548-13558). IEEE Computer Society. https://doi.org/10.48550/arXiv.2402.08657, https://doi.org/10.1109/CVPR52733.2024.01286
  • Open Access
    Zhang, Y., Doughty, H., & Snoek, C. G. M. (2024). Low-Resource Vision Challenges for Foundation Models. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition: CVPR 2024 : Seattle, Washington, USA, 16-22 June 2024 : proceedings (pp. 21956-21966). IEEE Computer Society. https://doi.org/10.48550/arXiv.2401.04716, https://doi.org/10.1109/CVPR52733.2024.02073
  • Open Access
    Hu, V. T., Zhang, W., Tang, M., Mettes, P., Zhao, D., & Snoek, C. (2024). Latent Space Editing in Transformer-Based Flow Matching. In M. Wooldridge, J. Dy, & S. Natarajan (Eds.), Proceedings of the 38th AAAI Conference on Artificial Intelligence: AAAI-2024 (Vol. 3, pp. 2247-2255). AAAI Press. https://doi.org/10.1609/aaai.v38i3.27998
  • Open Access
    Rastegar, S., Doughty, H., & Snoek, C. G. M. (2024). Background no more: Action recognition across domains by causal interventions. Computer Vision and Image Understanding, 242, Article 103975. https://doi.org/10.1016/j.cviu.2024.103975
  • Open Access
    Du, Y., Sun, H., Zhen, X., Xu, J., Yin, Y., Shao, L., & Snoek, C. G. M. (2024). MetaKernel: Learning Variational Random Features With Limited Labels. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(3), 1464-1478. https://doi.org/10.1109/TPAMI.2022.3154930
  • Open Access
    Shi, Z., Mettes, P., & Snoek, C. G. M. (2024). Focus for Free in Density-Based Counting. International Journal of Computer Vision, 132(7), 2600-2617. https://doi.org/10.1007/s11263-024-01990-3
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