Christophe Cerisara

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 50 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it
• Natural Language Processing — 21 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Model Architectures — 9 citations into it

Whom Christophe Cerisara trusts overall

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

1. Yann LeCun
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Ronan Collobert
6. Yoon Kim
7. Karen Simonyan
8. Alex Krizhevsky
9. Thorsten Joachims
10. Ilya Sutskever

Papers from Christophe Cerisara's perspective

Ordered by how strongly the researchers Christophe Cerisara 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Do Convolutional Networks need to be Deep for Text Classification ? (2017) — 108 citations