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Results: 5
Number of items: 5
  • 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
    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
    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
    Hu, V. T., Zhang, D. W., Asano, Y. M., Burghouts, G. J., & Snoek, C. G. M. (2023). Self-Guided Diffusion Models. In CVPR 2023: proceedings: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition : Vancouver, Canada : 18-22 June 2023 (pp. 18413-18422). IEEE Computer Society. https://doi.org/10.48550/arXiv.2210.06462, https://doi.org/10.1109/CVPR52729.2023.01766
  • Open Access
    Zhang, D. W., Burghouts, G. J., & Snoek, C. G. M. (2022). Pruning Edges and Gradients to Learn Hypergraphs from Larger Sets. Proceedings of Machine Learning Research, 198, Article 53. https://doi.org/10.48550/arXiv.2106.13919
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