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Results: 56
Number of items: 56
  • Open Access
    Giri, C., Granmo, O. C., & Van Hoof, H. (2024). Accelerated Tsetlin Machine Inference Through Incremental Model Re-evaluation. In 2024 International Symposium on the Tsetlin Machine (ISTM 2024): Pittsburgh, Pennsylvania, USA, 28-30 August 2024 (pp. 93-100). IEEE. https://doi.org/10.1109/ISTM62799.2024.10931270
  • Open Access
    García Satorras, V. (2024). Inductive biases for graph neural networks. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Huang, J. (2024). Learning recommender systems from biased user interactions. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Bakker, T. B. (2024). Learning adaptive sensing and active learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Chen, N., Mayol-Cuevas, W. W., Karl, M., Aljalbout, E., Zeng, A., Cortese, A., Burgard, W., & van Hoof, H. (2023). Editorial: Language, affordance and physics in robot cognition and intelligent systems. Frontiers in Robotics and AI, 10, Article 1355576. https://doi.org/10.3389/frobt.2023.1355576
  • Open Access
    Kuric, D., & van Hoof, H. (2023). Reusable Options through Gradient-based Meta Learning. Transactions on Machine Learning Research, 2023(3), Article 717. https://openreview.net/forum?id=qdDmxzGuzu
  • Open Access
    Keller, T. A. (2023). Natural inductive biases for artificial intelligence. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Bakker, T., van Hoof, H., & Welling, M. (2023). Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes. In D. Koutra, C. Plant, M. Gomez Rodriguez, E. Baralis, & F. Bonchi (Eds.), Machine Learning and Knowledge Discovery in Databases : Research Track : European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023 : proceedings (Vol. I, pp. 3-19). (Lecture Notes in Computer Science; Vol. 14169), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.48550/arXiv.2309.05477, https://doi.org/10.1007/978-3-031-43412-9_1
  • Open Access
    van der Pol, E. (2023). Symmetry and structure in deep reinforcement learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Wöhlke, J., Schmitt, F., & van Hoof, H. (2023). Learning Hierarchical Planning-Based Policies from Offline Data. In D. Koutra, C. Plant, M. Gomes Rodriguez, E. Baralis, & F. Bonchi (Eds.), Machine Learning and Knowledge Discovery in Databases: Research Track : European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023 : proceedings (Vol. IV, pp. 489–505). (Lecture Notes in Computer Science; Vol. 14172), ( Lecture Notes in Artificial Intelligence ). Springer. https://doi.org/10.1007/978-3-031-43421-1_29
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