Jamie Ray

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 2 papers; trusts 270 researchers and is trusted by 491 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 79 citations into it; #1,911 of 21,575 by trust here, #3,141 by citations
• Artificial Intelligence — 47 citations into it; #9,164 of 35,345 by trust here, #4,923 by citations
• Model Architectures — 17 citations into it
• 3D Vision & Pose — 5 citations into it

Whom Jamie Ray trusts overall

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

1. Kaiming He
2. Christian Szegedy
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. Karen Simonyan
7. Sergey Ioffe
8. Andrew Zisserman
9. X. Zhang
10. Ross B. Girshick

Who trusts Jamie Ray overall

1. Bruno Korbar
2. Rohit Girdhar
3. Limin Wang
4. Du Tran
5. Lorenzo Torresani
6. Ali Diba
7. Saining Xie
8. Christoph Feichtenhofer
9. Amir Ghodrati
10. Yunpeng Chen

Papers from Jamie Ray's perspective

Ordered by how strongly the researchers Jamie Ray 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A Closer Look at Spatiotemporal Convolutions for Action Recognition (2017) — 3,656 citations
• ConvNet Architecture Search for Spatiotemporal Feature Learning (2017) — 417 citations