Vincent François-Lavet

Artificial Intelligence · with Huang · 2019

A researcher in the Science corpus: 1 paper; trusts 24 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it; #27,560 of 35,345 by trust here, #33,294 by citations
• Computer Vision and Pattern Recognition — 10 citations into it
• Optimization & Training — 5 citations into it
• Reinforcement Learning — 5 citations into it

Whom Vincent François-Lavet trusts overall

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

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

Who trusts Vincent François-Lavet overall

1. Yaoyao Liu

Papers from Vincent François-Lavet's perspective

Ordered by how strongly the researchers Vincent François-Lavet 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Neural Architecture Search for Class-incremental Learning (2019) — 20 citations