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Results: 111
Number of items: 111
  • Kofinas, M., Bekkers, E., Nagaraja, N. S., & Gavves, S. (2023, December 13). Electrostatic field dataset - Latent Field Discovery in Interacting Dynamical Systems with Neural Fields [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10631646
  • Trémuel, P. G., Gavves, E., Würsch, C., Frick, K., & Vetsch, R. (2023). Parameter-free Neural Field-based Optimal Design of Nonuniform Transmission Lines. In ICECS 2023: 2023 30th IEEE International Conference on Electronics, Circuits and Systems (ICECS) : 4-7 December 2023, Hilton Maslak İstanbul, Turkey (pp. 211-214). IEEE. https://doi.org/10.1109/ICECS58634.2023.10382765
  • Open Access
    Kofinas, M., Bekkers, E. J., Nagaraja, N. S., & Gavves, E. (2023). Latent Field Discovery in Interacting Dynamical Systems with Neural Fields. 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/6521bd47ebaa28228cd6c74cb85afb65-Abstract-Conference.html
  • Open Access
    Gabel, A., Klein, V., Valperga, R., Lamb, J. S. W., Webster, K., Quax, R., & Gavves, E. (2023). Learning Lie Group Symmetry Transformations with Neural Networks. Proceedings of Machine Learning Research, 221, 50-59. https://proceedings.mlr.press/v221/gabel23a.html
  • Open Access
    Lippe, P., Magliacane, S., Löwe, S., Asano, Y. M., Cohen, T., & Gavves, E. (2023). BISCUIT: Causal Representation Learning from Binary Interactions. Proceedings of Machine Learning Research, 216, 1263-1273. https://proceedings.mlr.press/v216/lippe23a.html
  • Open Access
    Bondesan, R., Gavves, E., Oh, C., & Welling, M. (2023). Batch Bayesian Optimization on Permutations using Acquisition Weighted Kernels. 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. 10, pp. 6843-6858). (Advances in Neural Information Processing Systems; Vol. 35). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper_files/paper/2022/hash/2d779258dd899505b56f237de66ae470-Abstract-Conference.html
  • Open Access
    Auzina, I. A., Yıldız, Ç., Magliacane, S., Bethge, M., & Gavves, E. (2023). Modulated Neural ODEs. 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/8bc74514d554a90c996576f6c373f5f3-Abstract-Conference.html
  • Open Access
    Yin, W., Sonke, J. J., & Gavves, E. (2023). PC-Reg: A pyramidal prediction–correction approach for large deformation image registration. Medical Image Analysis, 90, Article 102978. https://doi.org/10.1016/j.media.2023.102978
  • Open Access
    Pervez, A. A. (2023). Structural constraints in neural network representations. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Oh, C. (2023). Bayesian optimization on non-conventional search spaces. [Thesis, fully internal, Universiteit van Amsterdam].
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