Yiru Shen

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 4 papers; trusts 292 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 101 citations into it
• Computational Mechanics — 73 citations into it; #1,870 of 10,001 by trust here, #826 by citations
• Graph Learning — 35 citations into it
• Aerospace Engineering — 32 citations into it
• Geology — 31 citations into it; #131 of 687 by trust here, #86 by citations
• Artificial Intelligence — 30 citations into it
• 3D Vision & Pose — 24 citations into it
• Model Architectures — 19 citations into it

Whom Yiru Shen trusts overall

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

1. Charles Ruizhongtai Qi
2. Yann LeCun
3. Geoffrey E. Hinton
4. Hao Su
5. Alex Krizhevsky
6. Yoshua Bengio
7. Roman Klokov
8. Kaiming He
9. Diederik P. Kingma
10. Gernot Riegler

Who trusts Yiru Shen overall

1. Pedro Hermosilla
2. Yifan Wang
3. Yaoqing Yang
4. Yongcheng Liu
5. Weiwei Sun
6. Zhiyuan Zhang
7. Xu Yan
8. Thang Vu
9. Yutong Feng
10. Tobias Ritschel

Papers from Yiru Shen's perspective

Ordered by how strongly the researchers Yiru Shen 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. 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation (2017) — 1,401 citations
• Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling (2017) — 532 citations
• Neighbors Do Help: Deeply Exploiting Local Structures of Point Clouds (2017) — 33 citations
• FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds (2017) — 84 citations