D. Chételat

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Computational Theory and Mathematics — 10 citations into it
• Reinforcement Learning — 7 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Industrial and Manufacturing Engineering — 5 citations into it

Whom D. Chételat trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Thorsten Joachims
4. C. Burges
5. Tobias Achterberg
6. Dean A. Pomerleau
7. Andrea Lodi
8. Geoffrey E. Hinton
9. Jimmy Ba
10. Yann LeCun

Papers from D. Chételat's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Reinforcement Learning: An Introduction
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Understanding the difficulty of training deep feedforward neural networks

Their papers

• Exact Combinatorial Optimization with Graph Convolutional Neural Networks (2019) — 647 citations