Julia Peyre

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 241 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 43 citations into it
• Artificial Intelligence — 23 citations into it
• Multimodal Learning — 15 citations into it

Whom Julia Peyre trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Li Fei-Fei
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Yoshua Bengio
7. Shaoqing Ren
8. Diederik P. Kingma
9. Yann LeCun
10. Ilya Sutskever

Who trusts Julia Peyre overall

1. Rakshith Shetty
2. François Plesse
3. Hyojin Bahng
4. Ji Zhang
5. Thomas Kerdreux
6. Bernt Schiele
7. Alexandru-Lucian Gînsca
8. Sanghyuk Chun

Papers from Julia Peyre's perspective

Ordered by how strongly the researchers Julia Peyre 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. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Weakly-Supervised Learning of Visual Relations (2017) — 200 citations