Beiträge in Tagungsbänden

de Colnet, A. (2024). On the Relative Efficiency of Dynamic and Static Top-Down Compilation to Decision-DNNF. In 27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024) (pp. 11:1-11:21). Schloss Dagstuhl. https://doi.org/10.4230/LIPIcs.SAT.2024.11 ( reposiTUm)
de Colnet, A., Szeider, S., & Zhang, T. (2024). Compilation and Fast Model Counting beyond CNF. In K. Larson (Ed.), Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (pp. 3315–3323). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2024/367 ( reposiTUm)
Chew, L., De Colnet, A., Slivovsky, F., & Szeider, S. (2024). Hardness of Random Reordered Encodings of Parity for Resolution and CDCL. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI ’24) (pp. 7978–7986). AAAI Press. https://doi.org/10.1609/aaai.v38i8.28635 ( reposiTUm)
de Colnet, A., & Marquis, P. (2023). On Translations between ML Models for XAI Purposes. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23) (pp. 3158–3166). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/352 ( reposiTUm)
De Colnet, A. (2023). Separating Incremental and Non-Incremental Bottom-Up Compilation. In M. Mahajan & F. Slivovsky (Eds.), 26th International Conference on Theory and Applications of Satisfiability Testing (SAT 2023). Schloss-Dagstuhl - Leibniz Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.SAT.2023.7 ( reposiTUm)