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Results: 3
Number of items: 3
  • Open Access
    Breuer, N. O., Sauter, A., Mohammadi, M., & Acar, E. (2024). CAGE: Causality-Aware Shapley Value for Global Explanations. In L. Longo, S. Lapuschkin, & C. Seifert (Eds.), Explainable Artificial Intelligence: Second World Conference, xAI 2024, Valletta, Malta, July 17–19, 2024 : proceedings (Vol. III, pp. 143–162). (Communications in Computer and Information Science; Vol. 2155). Springer. https://doi.org/10.1007/978-3-031-63800-8_8
  • Open Access
    Sauter, A., Boteghi, N., Acar, E., & Plaat, A. (2024). CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning. In AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems : May 6-10, 2024, Auckland, New Zealand (pp. 1664-1672). International Foundation for Autonomous Agents and Multiagent Systems. https://www.ifaamas.org/Proceedings/aamas2024/pdfs/p1664.pdf
  • Open Access
    Sauter, A., Acar, E., & François-Lavet, V. (2023). A Meta-Reinforcement Learning Algorithm for Causal Discovery. Proceedings of Machine Learning Research, 213, 602-619. https://doi.org/10.48550/arXiv.2207.08457
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