Didier Chételat

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 24

Top Topics

Combinatorial Optimization

Branch And Bound

Change Point Detection

Top Venues

J. Multivar. Anal.

Publications

Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan
GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection. KDD (2024)
Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan
GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection. CoRR (2024)
Chendi Qian, Didier Chételat, Christopher Morris
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems. AISTATS (2024)
Didier Chételat, Andrea Lodi
Continuous cutting plane algorithms in integer programming. Oper. Res. Lett. 51 (4) (2023)
Chendi Qian, Didier Chételat, Christopher Morris
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems. CoRR (2023)
Rafael Sterzinger, Jan Poland, Max B. Paulus, Didier Chételat
Learning to Predict Security Constraints for Large-Scale Unit Commitment Problems. ISGT EUROPE (2023)
Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic
Combinatorial Optimization and Reasoning with Graph Neural Networks. J. Mach. Learn. Res. 24 (2023)
Lara Scavuzzo, Feng Yang Chen, Didier Chételat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen Aardal
Learning to Branch with Tree MDPs. NeurIPS (2022)
Abdel Ghani Labassi, Didier Chételat, Andrea Lodi
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks. CoRR (2022)
Prateek Gupta, Elias B. Khalil, Didier Chételat, Maxime Gasse, Yoshua Bengio, Andrea Lodi, M. Pawan Kumar
Lookback for Learning to Branch. CoRR (2022)
Lara Scavuzzo, Feng Yang Chen, Didier Chételat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen Aardal
Learning to branch with Tree MDPs. CoRR (2022)
Prateek Gupta, Elias Boutros Khalil, Didier Chételat, Maxime Gasse, Andrea Lodi, Yoshua Bengio, M. Pawan Kumar
Lookback for Learning to Branch. Trans. Mach. Learn. Res. 2022 (2022)
Maxime Gasse, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias B. Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yangm, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Chen Binbin, He Minggui, Hao Hao, Zhang Zhiyu, An Zhiwu, Mao Kun
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. CoRR (2022)
Abdel Ghani Labassi, Didier Chételat, Andrea Lodi
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks. NeurIPS (2022)
Antoine Prouvost, Justin Dumouchelle, Maxime Gasse, Didier Chételat, Andrea Lodi
Ecole: A Library for Learning Inside MILP Solvers. CoRR (2021)
Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic
Combinatorial Optimization and Reasoning with Graph Neural Networks. IJCAI (2021)
Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic
Combinatorial optimization and reasoning with graph neural networks. CoRR (2021)
Maxime Gasse, Simon Bowly, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yang, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Binbin Chen, Minggui He, Hao Hao, Zhiyu Zhang, Zhiwu An, Kun Mao
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. NeurIPS (Competition and Demos) (2021)
Antoine Prouvost, Justin Dumouchelle, Lara Scavuzzo, Maxime Gasse, Didier Chételat, Andrea Lodi
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers. CoRR (2020)
Aurélien Serre, Didier Chételat, Andrea Lodi
Change Point Detection by Cross-Entropy Maximization. CoRR (2020)
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi
Exact Combinatorial Optimization with Graph Convolutional Neural Networks. CoRR (2019)
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi
Exact Combinatorial Optimization with Graph Convolutional Neural Networks. NeurIPS (2019)
Didier Chételat, Rajendran Narayanan, Martin T. Wells
On the domain of attraction of a Tracy-Widom law with applications to testing multiple largest roots. J. Multivar. Anal. 165 (2018)
Didier Chételat, Martin T. Wells
Improved second order estimation in the singular multivariate normal model. J. Multivar. Anal. 147 (2016)