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2020 – today
- 2024
[c8]Chendi Qian, Didier Chételat, Christopher Morris:
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems. AISTATS 2024: 1432-1440- [c7]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: 6301-6311 - [i11]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 abs/2405.11024 (2024) - 2023
- [j5]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: 130:1-130:61 (2023) - [j4]Didier Chételat, Andrea Lodi:
Continuous cutting plane algorithms in integer programming. Oper. Res. Lett. 51(4): 439-445 (2023) - [c6]Rafael Sterzinger, Jan Poland, Max B. Paulus, Didier Chételat:
Learning to Predict Security Constraints for Large-Scale Unit Commitment Problems. ISGT EUROPE 2023: 1-5 - [i10]Chendi Qian, Didier Chételat, Christopher Morris:
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems. CoRR abs/2310.10603 (2023) - 2022
- [j3]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) - [c5]Abdel Ghani Labassi, Didier Chételat, Andrea Lodi:
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks. NeurIPS 2022 - [c4]Lara Scavuzzo, Feng Yang Chen, Didier Chételat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen I. Aardal:
Learning to Branch with Tree MDPs. NeurIPS 2022 - [i9]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 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. CoRR abs/2203.02433 (2022) - [i8]Lara Scavuzzo, Feng Yang Chen, Didier Chételat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen I. Aardal:
Learning to branch with Tree MDPs. CoRR abs/2205.11107 (2022) - [i7]Prateek Gupta, Elias B. Khalil, Didier Chételat, Maxime Gasse, Yoshua Bengio, Andrea Lodi, M. Pawan Kumar:
Lookback for Learning to Branch. CoRR abs/2206.14987 (2022) - [i6]Abdel Ghani Labassi, Didier Chételat, Andrea Lodi:
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks. CoRR abs/2210.16934 (2022) - 2021
- [c3]Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic:
Combinatorial Optimization and Reasoning with Graph Neural Networks. IJCAI 2021: 4348-4355 - [c2]Maxime Gasse, Simon Bowly, 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 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: 220-231 - [i5]Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic:
Combinatorial optimization and reasoning with graph neural networks. CoRR abs/2102.09544 (2021) - [i4]Antoine Prouvost, Justin Dumouchelle, Maxime Gasse, Didier Chételat, Andrea Lodi:
Ecole: A Library for Learning Inside MILP Solvers. CoRR abs/2104.02828 (2021) - 2020
- [i3]Aurélien Serre, Didier Chételat, Andrea Lodi:
Change Point Detection by Cross-Entropy Maximization. CoRR abs/2009.01358 (2020) - [i2]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 abs/2011.06069 (2020)
2010 – 2019
- 2019
- [c1]Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi:
Exact Combinatorial Optimization with Graph Convolutional Neural Networks. NeurIPS 2019: 15554-15566 - [i1]Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi:
Exact Combinatorial Optimization with Graph Convolutional Neural Networks. CoRR abs/1906.01629 (2019) - 2018
- [j2]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: 132-142 (2018) - 2016
- [j1]Didier Chételat, Martin T. Wells:
Improved second order estimation in the singular multivariate normal model. J. Multivar. Anal. 147: 1-19 (2016)
Coauthor Index
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last updated on 2024-09-22 00:38 CEST by the dblp team
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