Alexis de Colnet
Projektass.(FWF) / PhD
Role
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PostDoc Researcher
Algorithms and Complexity, E192-01
Projects
Publications
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Hardness of Random Reordered Encodings of Parity for Resolution and CDCL
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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
Project: Overcoming Intractability in the Knowledge Compilation Map (2022–2025) -
Compilation and Fast Model Counting beyond CNF
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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
Project: Overcoming Intractability in the Knowledge Compilation Map (2022–2025) -
ASP-QRAT: A Conditionally Optimal Dual Proof System for ASP
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Chew, L., de Colnet, A., & Szeider, S. (2024). ASP-QRAT: A Conditionally Optimal Dual Proof System for ASP. In P. Marquis, M. Ortiz, & M. Pagnucco (Eds.), Proceedings of the TwentyFirst International Conference on Principles of Knowledge Representation and Reasoning (pp. 253–263). https://doi.org/10.24963/kr.2024/24
Project: QBFPC (2022–2025) -
On the Relative Efficiency of Dynamic and Static Top-Down Compilation to Decision-DNNF
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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
Download: On the Relative Efficiency of Dynamic and Static Top-Down Compilation to Decision-DNNF (920 KB)
Project: Overcoming Intractability in the Knowledge Compilation Map (2022–2025) -
Separating Incremental and Non-Incremental Bottom-Up Compilation
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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
Download: PDF (684 KB)
Project: Overcoming Intractability in the Knowledge Compilation Map (2022–2025) -
Characterizing Tseitin-formulas with short regular resolution refutations
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De Colnet, A., & Mengel, S. (2023). Characterizing Tseitin-formulas with short regular resolution refutations. Journal of Artificial Intelligence Research, 76, 265–286. https://doi.org/10.1613/jair.1.13521
Download: PDF (351 KB) -
On Translations between ML Models for XAI Purposes
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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
Download: PDF (205 KB)
Project: Overcoming Intractability in the Knowledge Compilation Map (2022–2025)