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Results: 56
Number of items: 56
  • 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
    Hoogeboom, E. (2023). Normalizing flows and diffusion models for discrete and geometric data. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Keller, T. A. (2023). Natural inductive biases for artificial intelligence. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Giri, C., Granmo, O.-C., van Hoof, H., & Blakely, C. D. (2022). Logic-based AI for Interpretable Board Game Winner Prediction with Tsetlin Machine. In 2022 International Joint Conference on Neural Networks (IJCNN): 2022 conference proceedings (pp. 5528-5536). IEEE. https://doi.org/10.1109/IJCNN55064.2022.9892796
  • Open Access
    Wöhlke, J., Schmitt, F., & van Hoof, H. (2022). Value Refinement Network (VRN). In L. De Raedt (Ed.), Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence: IJCAI 2022, Vienna, Austria, 23-29 July 2022 (pp. 3558-3565). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2022/494
  • Open Access
    Höpner, N., Tiddi, I., & van Hoof, H. (2022). Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methods. In L. De Raedt (Ed.), Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence: IJCAI 2022, Vienna, Austria, 23-29 July 2022 (pp. 3050-3056). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2022/423
  • Open Access
    Wang, Q., & van Hoof, H. (2022). Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search. Proceedings of Machine Learning Research, 162, 23055-23077. https://proceedings.mlr.press/v162/wang22z.html
  • Open Access
    Long, A., Blair, A., & van Hoof, H. (2022). Fast and Data Efficient Reinforcement Learning from Pixels via Non-Parametric Value Approximation. In K. Sycara, V. Honavar, & M. Spaan (Eds.), Proceedings of the 36th AAAI Conference on Artificial Intelligence: AAAI-22 : virtual conference, Vancouver, Canada, February 22-March 1, 2022 (Vol. 7, pp. 7620-7627). AAAI Press. https://doi.org/10.1609/aaai.v36i7.20728
  • Open Access
    Wang, Q. (2022). Functional representation learning for uncertainty quantification and fast skill transfer. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Kool, W. (2022). Learning and optimization in combinatorial spaces: With a focus on deep learning for vehicle routing. [Thesis, fully internal, Universiteit van Amsterdam].
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