Didier Chételat
- Research Scientist, Polytechnique Montréal
- didier.chetelat@polymtl.ca
I'm a machine learning researcher at the Canada Excellence Research Chair in Data Science for Real Time
Decision Making, under the leadership of Andrea Lodi.
I obtained my Ph.D. in Statistics at Cornell University in 2015 under the supervision of Martin T. Wells.
My main research interests center around deep learning for combinatorial optimization. I also work on applied projects, most recently in finance, transportation, medical imaging and physical engineering.
My main research interests center around deep learning for combinatorial optimization. I also work on applied projects, most recently in finance, transportation, medical imaging and physical engineering.
Publications
2019
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Exact combinatorial optimization with graph convolutional neural networks
Advances in Neural Information Processing Systems 32, 15554–15566. Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi [code] -
The middle-scale asymptotics of Wishart matrices
Annals of Statistics 47, 2639-2670. Didier Chételat, Martin T. Wells
2018
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On the domain of attraction of a Tracy–Widom law with applications to testing multiple largest roots
Journal of Multivariate Analysis 165, 132-142. Didier Chételat, Rajendran Narayanan, Martin T. Wells
2017
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Optimal two-step prediction in regression
Electronic Journal of Statistics 11, 2519-2546. Didier Chételat, Joseph Salmon, Johannes Lederer
2016
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Improved second order estimation in the singular multivariate normal model
Journal of Multivariate Analysis 147, 1-19. Didier Chételat, Martin T. Wells
2012
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Improved multivariate normal mean estimation with unknown covariance when p is greater than n
Annals of Statistics 40, 3137-3160. Didier Chételat, Martin T. Wells