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Results: 6
Number of items: 6
  • Open Access
    Xiao, Z. (2025). Learning to generalize at test time. [Thesis, fully internal, Universiteit van Amsterdam].
  • 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
    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
    Shen, J., Snoek, C., Worring, M., Xiao, Z., & Zhen, X. (2023). Association Graph Learning for Multi-Task Classification with Category Shifts. 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. 7, pp. 4503-4516). (Advances in Neural Information Processing Systems; Vol. 35). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper_files/paper/2022/hash/1cc70be9fb6a83bc46cf4ac21a91e0b0-Abstract-Conference.html
  • Open Access
    Xiao, Z., Shen, J., Zhen, X., Shao, L., & Snoek, C. G. M. (2021). A Bit More Bayesian: Domain-Invariant Learning with Uncertainty. Proceedings of Machine Learning Research, 139, 11351-11361. https://proceedings.mlr.press/v139/xiao21a.html
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