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Results: 298
Number of items: 298
  • Open Access
    Hu, T., Thong, W., Mettes, P., & Snoek, C. G. M. (2023). Query by Activity Video in the Wild. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2311.13895
  • Open Access
    Sun, W., Du, Y., Zhen, X., Wang, F., Wang, L., & Snoek, C. G. M. (2023). MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks. Proceedings of Machine Learning Research, 202, 32847-32858. https://proceedings.mlr.press/v202/sun23b.html
  • Open Access
    Jing, M., Zhen, X., Li, J., & Snoek, C. G. M. (2023). Order-preserving Consistency Regularization for Domain Adaptation and Generalization. In 2023 IEEE/CVF International Conference on Computer Vision: ICCV 2023 : Paris, France, 2-6 October 2023 : proceedings (pp. 18870-18881). IEEE Computer Society. https://doi.org/10.48550/arXiv.2309.13258, https://doi.org/10.1109/ICCV51070.2023.01734
  • Open Access
    Zhang, Y., Zhang, D. W., Lacoste-Julien, S., Burghouts, G. J., & Snoek, C. G. M. (2023). Unlocking Slot Attention by Changing Optimal Transport Costs. Proceedings of Machine Learning Research, 202, 41931-41951. https://proceedings.mlr.press/v202/zhang23ba.html
  • Open Access
    Bagad, P., Tapaswi, M., & Snoek, C. G. M. (2023). Test of Time: Instilling Video-Language Models with a Sense of Time. In CVPR 2023: proceedings: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition : Vancouver, Canada : 18-22 June 2023 (pp. 2503-2516). IEEE Computer Society. https://doi.org/10.48550/arXiv.2301.02074, https://doi.org/10.1109/CVPR52729.2023.00247
  • Open Access
    Du, Y., Xiao, Z., Liao, S., & Snoek, C. G. M. (2023). ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion. 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/911dd89c81efc624c4e1c39381179505-Abstract-Conference.html
  • Open Access
    Du, Y., Shen, J., Zhen, X., & Snoek, C. G. M. (2023). SuperDisco: Super-Class Discovery Improves Visual Recognition for the Long-Tail. In CVPR 2023: proceedings: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition : Vancouver, Canada : 18-22 June 2023 (pp. 19944-19954). IEEE Computer Society. https://doi.org/10.48550/arXiv.2304.00101, https://doi.org/10.1109/CVPR52729.2023.01910
  • Open Access
    Rastegar, S., Doughty, H., & Snoek, C. G. M. (2023). Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery. 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/e6789e468c65a7816760a00a487d3c4e-Abstract-Conference.html
  • Open Access
    Jing, M., Li, J., Snoek, C., & Zhen, X. (2023). Variational Model Perturbation for Source-Free Domain Adaptation. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), 36th Conference on Neural Information Processing Systems (NeurIPS 2022): New Orleans, Louisiana, USA, 28 November-9 December 2022 (Vol. 23, pp. 17173-17187). (Advances in Neural Information Processing Systems; Vol. 35). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper_files/paper/2022/hash/6d7a9f292360193eb530d693f7941c73-Abstract-Conference.html
  • Open Access
    Pervez, A. A. (2023). Structural constraints in neural network representations. [Thesis, fully internal, Universiteit van Amsterdam].
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