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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Boisvert, L., Verhaeghe, H., & Cappart, Q. (2024, May). Towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches [Paper]. 21st International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2024), Uppsala, Sweden. External link
Pesant, G., Quimper, C.-G., & Verhaeghe, H. (2022, June). Practically uniform solution sampling in constraint programming [Paper]. 19th International Conference on Integration of Constraint Programming, Artificial Intelligence and Operations Research (CPAIOR 2022), Los Angeles, CA, USA. External link
Verhaeghe, H., Cappart, Q., Pesant, G., & Quimper, C.-G. (2025, June). Apprentissage de précédences pour des problèmes de planification avec des réseaux de neurones en graphes [Paper]. Plate-Forme Intelligence Artificielle (PFIA'25), Dijon, France (3 pages). External link
Verhaeghe, H., Cappart, Q., Pesant, G., & Quimper, C.-G. (2024, September). Learning Precedences for Scheduling Problems with Graph Neural Networks [Paper]. 30th International Conference on Principles and Practice of Constraint Programming (CP 2024), Girona, Spain (18 pages). External link
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2021, June). Learning Optimal Decision Trees using Constraint Programming [Paper]. 16th French-Speaking Conference on Constraint Programming (JFPC 2021). Unavailable
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2020). Learning optimal decision trees using constraint programming. Constraints, 25(3-4), 226-250. External link
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2021, January). Learning optimal decision trees using constraint programming (extended abstract) [Paper]. 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), Yokohama, Japan. External link
