Search results
Results: 71
Number of items: 71
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Valenzuela, R. E. G., Mettes, P., Loos, B., Marquering, H., & Berkhout, E. (2024). Enhancement of early proximal caries annotations in radiographs: introducing the Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset. BMC Oral Health, 24, Article 1325. https://doi.org/10.1186/s12903-024-05076-x -
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 -
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 -
D’Amely di Melendugno, G. M., Flaborea, A., Mettes, P., & Galasso, F. (2024). Hyp2Nav: Hyperbolic Planning and Curiosity for Crowd Navigation. In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems: IROS'24, Abu Dhabi, 14-18 October 2024 (pp. 13023–13030). IEEE. https://doi.org/10.1109/iros58592.2024.10801513 -
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 -
Mettes, P., Ghadimi Atigh, M., Keller-Ressel, M., Gu, J., & Yeung, S. (2024). Hyperbolic Deep Learning in Computer Vision: A Survey. International Journal of Computer Vision, 132(9), 3484-3508. https://doi.org/10.1007/s11263-024-02043-5 -
Ibrahimi, S., Ghadimi Atigh, M., van Noord, N., Mettes, P., & Worring, M. (2024). Intriguing Properties of Hyperbolic Embeddings in Vision-Language Models. Transactions on Machine Learning Research, 2024, Article 2113. https://openreview.net/forum?id=P5D2gfi4Gg -
Mettes, P. (2023). Hyperbolic Graph Codebooks. In G. Nicosia, V. Ojha, E. La Malfa, G. La Malfa, P. Pardalos, G. Di Fatta, G. Giuffrida, & R. Umeton (Eds.), Machine Learning, Optimization, and Data Science: 8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 19–22, 2022, Revised Selected Papers (Vol. I, pp. 48-61). (Lecture Notes in Computer Science; Vol. 13810). Springer. https://doi.org/10.1007/978-3-031-25599-1_5
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Mettes, P. (2023). Universal Prototype Transport for Zero-Shot Action Recognition and Localization. International Journal of Computer Vision, 131(11), 3060-3073. https://doi.org/10.1007/s11263-023-01846-2 -
Burghouts, G., Cucchiara, R., Kasarla, T., Mettes, P., Van Der Pol, E., & Van Spengler, M. (2023). Maximum Class Separation as Inductive Bias in One Matrix. 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. 26, pp. 19553-19566). (Advances in Neural Information Processing Systems; Vol. 35). Neural Information Processing Systems Foundation. https://doi.org/10.48550/arXiv.2206.08704
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