Didier Chételat

30 papers A* 6A 2Journal 20Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Balanced Neuro-Symbolic Approach for Commonsense Abductive Logic.
CoRR
Joseph Cotnareanu, Didier Chételat, Yingxue Zhang, Mark Coates
2025 A conf
InnerThoughts: Disentangling Representations and Predictions in Large Language Models.
AISTATS
Didier Chételat, Joseph Cotnareanu, Rylee Thompson, Yingxue Zhang, Mark Coates
2025 J jnl
InnerThoughts: Disentangling Representations and Predictions in Large Language Models.
CoRR
Didier Chételat, Joseph Cotnareanu, Rylee Thompson, Yingxue Zhang, Mark Coates
2025 A* conf
The Graph's Apprentice: Teaching an LLM Low-Level Knowledge for Circuit Quality Estimation.
IJCAI
Reza Moravej, Saurabh Bodhe, Zhanguang Zhang, Didier Chételat, Dimitrios Tsaras, Yingxue Zhang, Hui-Ling Zhen, Jianye Hao, Mingxuan Yuan
2024 A conf
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems.
AISTATS
Chendi Qian, Didier Chételat, Christopher Morris
2024 A* conf
GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection.
KDD
Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan
2024 J jnl
GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection.
CoRR
Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan
2024 J jnl
Hint Marginalization for Improved Reasoning in Large Language Models.
CoRR
Soumyasundar Pal, Didier Chételat, Yingxue Zhang, Mark Coates
2024 J jnl
The Graph's Apprentice: Teaching an LLM Low Level Knowledge for Circuit Quality Estimation.
CoRR
Reza Moravej, Saurabh Bodhe, Zhanguang Zhang, Didier Chételat, Dimitrios Tsaras, Yingxue Zhang, Hui-Ling Zhen, Jianye Hao, Mingxuan Yuan
2023 J jnl
Combinatorial Optimization and Reasoning with Graph Neural Networks.
J. Mach. Learn. Res.
Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic
2023 J jnl
Continuous cutting plane algorithms in integer programming.
Oper. Res. Lett.
Didier Chételat, Andrea Lodi
2023 J jnl
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems.
CoRR
Chendi Qian, Didier Chételat, Christopher Morris
2023 — conf
Learning to Predict Security Constraints for Large-Scale Unit Commitment Problems.
ISGT EUROPE
Rafael Sterzinger, Jan Poland, Max B. Paulus, Didier Chételat
2022 A* conf
Learning to Branch with Tree MDPs.
NeurIPS
Lara Scavuzzo, Feng Yang Chen, Didier Chételat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen I. Aardal
2022 A* conf
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks.
NeurIPS
Abdel Ghani Labassi, Didier Chételat, Andrea Lodi
2022 J jnl
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks.
CoRR
Abdel Ghani Labassi, Didier Chételat, Andrea Lodi
2022 J jnl
Learning to branch with Tree MDPs.
CoRR
Lara Scavuzzo, Feng Yang Chen, Didier Chételat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen I. Aardal
2022 J jnl
Lookback for Learning to Branch.
CoRR
Prateek Gupta, Elias B. Khalil, Didier Chételat, Maxime Gasse, Yoshua Bengio, Andrea Lodi, M. Pawan Kumar
2022 J jnl
Lookback for Learning to Branch.
Trans. Mach. Learn. Res.
Prateek Gupta, Elias Boutros Khalil, Didier Chételat, Maxime Gasse, Andrea Lodi, Yoshua Bengio, M. Pawan Kumar
2022 J jnl
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.
CoRR
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
2021 A* conf
Combinatorial Optimization and Reasoning with Graph Neural Networks.
IJCAI
Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic
2021 J jnl
Combinatorial optimization and reasoning with graph neural networks.
CoRR
Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic
2021 J jnl
Ecole: A Library for Learning Inside MILP Solvers.
CoRR
Antoine Prouvost, Justin Dumouchelle, Maxime Gasse, Didier Chételat, Andrea Lodi
2021 — conf
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights.
NeurIPS (Competition and Demos)
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
2020 J jnl
Change Point Detection by Cross-Entropy Maximization.
CoRR
Aurélien Serre, Didier Chételat, Andrea Lodi
2020 J jnl
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers.
CoRR
Antoine Prouvost, Justin Dumouchelle, Lara Scavuzzo, Maxime Gasse, Didier Chételat, Andrea Lodi
2019 A* conf
Exact Combinatorial Optimization with Graph Convolutional Neural Networks.
NeurIPS
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi
2019 J jnl
Exact Combinatorial Optimization with Graph Convolutional Neural Networks.
CoRR
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi
2018 J jnl
On the domain of attraction of a Tracy-Widom law with applications to testing multiple largest roots.
J. Multivar. Anal.
Didier Chételat, Rajendran Narayanan, Martin T. Wells
2016 J jnl
Improved second order estimation in the singular multivariate normal model.
J. Multivar. Anal.
Didier Chételat, Martin T. Wells