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Results: 156
Number of items: 156
  • Open Access
    Igashov, I., Stärk, H., Vignac, C., Schneuing, A., Satorras, V. G., Frossard, P., Welling, M., Bronstein, M., & Correia, B. (2024). Equivariant 3D-conditional diffusion model for molecular linker design. Nature Machine Intelligence, 6(4), 417–427. https://doi.org/10.1038/s42256-024-00815-9
  • Open Access
    Esmaeili, B. (2024). Learning useful representations with variational autoencoders. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Schneuing, A., Harris, C., Du, Y., Didi, K., Jamasb, A., Igashov, I., Du, W., Gomes, C., Blundell, T. L., Lio, P., Welling, M., Bronstein, M., & Correia, B. (2024). Structure-based drug design with equivariant diffusion models. Nature Computational Science, 4(12), 899-909. https://doi.org/10.1038/s43588-024-00737-x
  • Open Access
    Wöhlke, J. G. (2024). Reinforcement learning and planning for autonomous agent navigation: With a focus on sparse reward settings. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Miller, B. K. (2024). Machine learning for scientific simulation: Inference and generative models. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    García Satorras, V. (2024). Inductive biases for graph neural networks. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Löwe, S. (2024). Learning structured representations of objects and relations. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Veeling, B. S. (2024). Deep learning for medical data. [Thesis, fully internal, Universiteitsbibliotheek].
  • Open Access
    Bakker, T. B. (2024). Learning adaptive sensing and active learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Weiler, M. (2024). Equivariant and coordinate independent convolutional networks: A gauge field theory of neural networks. [Thesis, fully internal, Universiteit van Amsterdam].
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