Quentin Fournier

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 164 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 90 citations into it
• Computer Vision and Pattern Recognition — 59 citations into it
• Model Architectures — 51 citations into it
• Natural Language Processing — 22 citations into it
• Efficiency & Compression — 21 citations into it
• Large Language Models — 16 citations into it
• Optimization & Training — 13 citations into it
• Signal Processing — 12 citations into it

Whom Quentin Fournier trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Alex Graves
4. Ilya Sutskever
5. Diederik P. Kingma
6. Alex Krizhevsky
7. Quoc V. Le
8. Kaiming He
9. Yann LeCun
10. Barret Zoph

Papers from Quentin Fournier's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• A Practical Survey on Faster and Lighter Transformers (2021) — 167 citations