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Results: 297
Number of items: 297
  • Open Access
    Du, Y. (2025). Learning to learn with less and less. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Nguyen, D.-K., Oswald, M. R., & Snoek, C. G. M. (2025). SimPLR: A Simple and Plain Transformer for Scaling-Efficient Object Detection and Segmentation. Transactions on Machine Learning Research, 2025, Article 3114. https://doi.org/10.48550/arXiv.2310.05920
  • Open Access
    Chen, A., Doughty, H., Li, X., & Snoek, C. G. M. (2025). Beyond Coarse-Grained Matching in Video-Text Retrieval. In M. Cho, I. Laptev, D. Tran, A. Yao, & H. Zha (Eds.), Computer Vision – ACCV 2024 : 17th Asian Conference on Computer Vision, Hanoi, Vietnam, December 8–12, 2024 : proceedings (Vol. III, pp. 25-43). (Lecture Notes in Computer Science ; Vol. 15474 ). Springer. https://doi.org/10.1007/978-981-96-0908-6_2
  • Open Access
    Xiao, Z. (2025). Learning to generalize at test time. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Bagad, P., Tapaswi, M., Snoek, C. G. M., & Zisserman, A. (2025). The Sound of Water: Inferring Physical Properties from Pouring Liquids. In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP): Hyderabad, India, 6-11 April 2025 (pp. 736-740). IEEE. https://doi.org/10.1109/ICASSP49660.2025.10889950
  • 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
    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
    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
    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
    Hu, V. T., Wu, D., Asano, Y. M., Mettes, P., Fernández-Méndez, F., Ommer, B., & Snoek, C. G. M. (2024). Flow Matching for Conditional Text Generation in a Few Sampling Steps. In Y. Graham, & M. Purver (Eds.), The 18th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference : EACL 2024 : March 17-22, 2024 (Vol. 2, pp. 380-392). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.eacl-short.33
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