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Results: 14
Number of items: 14
  • Open Access
    Nguyen, L., Boersma, M., & Acar, E. (2026). Detecting Fraud in Financial Networks: A Semi-Supervised GNN Approach with Granger-Causal Explanations. In R. Guidotti, U. Schmid, & L. Longo (Eds.), Explainable Artificial Intelligence: Third World Conference, xAI 2025, Istanbul, Turkey, July 9–11, 2025 : proceedings (Vol. IV, pp. 330–353). (Communications in Computer and Information Science; Vol. 2579). Springer. https://doi.org/10.1007/978-3-032-08330-2_16
  • Open Access
    Fonseca, J., Lô, G., Acar, E., & Santos, F. (2026). The Interplay between Media, Politics, and Online Behaviour: Measuring the Dynamics of Discriminatory Climates: Research for the State Commission against Discrimination and Racism. SIAS Research Group, Informatics Institute, Faculty of Science, University of Amsterdam. https://www.staatscommissietegendiscriminatieenracisme.nl/documenten/2026/02/11/voortgangsrapportage---tussen-kamer-krant-en-sociale-media
  • Open Access
    Chatterji, S., & Acar, E. (2025). Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement Learning. In I. Lynce, N. Murano, M. Vallati, S. Villata, F. Chesani, M. Milano, A. Omicini, & M. Dastani (Eds.), ECAI 2025: 28th European Conference on Artificial Intelligence, 25-30 October2025, Bologna, Italy : including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025) : proceedings (pp. 2538-2545). (Frontiers in Artificial Intelligence and Applications; Vol. 413). IOS Press. https://doi.org/10.48550/arXiv.2411.04867, https://doi.org/10.3233/FAIA251103
  • Open Access
    Zhang, T., Williams, A., Wozny, P., Cohrs, K.-H., Ponse, K., Jiralerspong, M., Phade, S. R., Srinivasa, S., Li, L., Zhang, Y., Gupta, P., Acar, E., Rish, I., Bengio, Y., & Zheng, S. (2025). AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N. Proceedings of Machine Learning Research, 267, 76332-76360. https://openreview.net/forum?id=PX29zF9wRb
  • Open Access
    Orzan, N., Acar, E., Grossi, D., & Rădulescu, R. (2025). Learning in public goods games: the effects of uncertainty and communication on cooperation. Neural Computing and Applications, 37(23), 18899–18932. https://doi.org/10.1007/s00521-024-10530-6
  • Open Access
    van Sprang, A., Acar, E., & Zuidema, W. (2024). Enforcing Interpretability in Time Series Transformers: A Concept Bottleneck Framework. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2410.06070
  • Open Access
    Orzan, N., Acar, E., Grossi, D., Mannion, P., & Rădulescu, R. (2024). Learning in Multi-Objective Public Goods Games with Non-Linear Utilities. In U. Endriss, F. S. Melo, K. Bach, A. Bugarín-Diz, J. M. Alonso-Moral, S. Barro, & F. Heintz (Eds.), ECAI 2024: 27th European Conference on Artificial Intelligence, 19–24 October 2024, Santiago de Compostela, Spain : including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024) : proceedings (pp. 2749-2756). (Frontiers in Artificial Intelligence and Applications; Vol. 392). IOS Press. https://doi.org/10.3233/FAIA240809
  • 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
    Orzan, N., Acar, E., Grossi, D., & Rădulescu, R. (2024). Emergent Cooperation under Uncertain Incentive Alignment. In AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems : May 6-10, 2024, Auckland, New Zealand (pp. 1521-1530). International Foundation for Autonomous Agents and Multiagent Systems. https://www.ifaamas.org/Proceedings/aamas2024/pdfs/p1521.pdf
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