Didier Chételat

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 81 citations into it
• Graph Learning — 30 citations into it
• Computer Vision and Pattern Recognition — 25 citations into it
• Computational Theory and Mathematics — 22 citations into it
• Model Architectures — 18 citations into it
• Reinforcement Learning — 18 citations into it
• Industrial and Manufacturing Engineering — 16 citations into it
• Management Science and Operations Research — 13 citations into it

Whom Didier Chételat trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yoshua Bengio
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Alex Graves
5. Richard S. Sutton
6. Max Welling
7. Yann LeCun
8. Ilya Sutskever
9. Alex Krizhevsky
10. Thorsten Joachims

Who trusts Didier Chételat overall

1. Yoshua Bengio

Papers from Didier Chételat's perspective

Ordered by how strongly the researchers Didier Chételat trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Exact Combinatorial Optimization with Graph Convolutional Neural Networks (2019) — 647 citations
• Combinatorial optimization and reasoning with graph neural networks (2021) — 498 citations