Search results
Results: 17
Number of items: 17
-
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 -
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
-
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
-
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
-
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
-
van Sprang, A., Samson, L., Lucic, A., Acar, E., Ghebreab, S., & Asano, Y. M. (2025). Same Content, Different Answers: Cross-Modal Inconsistency in MLLMs. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2512.08923
-
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
-
Sauter, A., Acar, E., & Plaat, A. (2024). Causal Playground: Addressing Data-Generation Requirements in Cutting-Edge Causality Research. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2405.13092
-
Visbeek, S., Acar, E., & den Hengst, F. (2024). Explainable Fraud Detection with Deep Symbolic Classification. 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. 350–373). (Communications in Computer and Information Science; Vol. 2155). Springer. https://doi.org/10.1007/978-3-031-63800-8_18
-
Azarm, C., Acar, E., & van Zeelt, M. (2024). On the Potential of Network-Based Features for Fraud Detection. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2402.09495
Page 1 of 2