Liyue Shen

Computer Vision and Pattern Recognition · 2015–2021

A researcher in the Science corpus: 5 papers; trusts 353 researchers and is trusted by 59 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 98 citations into it; #3,679 of 21,575 by trust here, #3,280 by citations
• Artificial Intelligence — 54 citations into it
• Radiology, Nuclear Medicine and Imaging — 33 citations into it; #3,140 of 3,265 by trust here, #2,914 by citations
• Computational Mechanics — 22 citations into it
• Multimodal Learning — 20 citations into it
• Generative Models — 16 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Biomedical Engineering — 12 citations into it; #10,324 of 10,734 by trust here, #9,539 by citations

Whom Liyue Shen trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Kaiming He
5. Yoshua Bengio
6. Ilya Sutskever
7. Yann LeCun
8. David G. Lowe
9. Jimmy Ba
10. Ross B. Girshick

Who trusts Liyue Shen overall

1. Liang Zheng
2. Zhedong Zheng
3. Hyungjin Chung
4. Yi Yang
5. Zhun Zhong
6. Kaiyang Zhou
7. Xiatian Zhu
8. Tao A. Xiang
9. Yifan Sun
10. Chi Su

Papers from Liyue Shen's perspective

Ordered by how strongly the researchers Liyue Shen 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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

• Scalable Person Re-identification: A Benchmark (2015) — 4,560 citations
• GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition (2021) — 567 citations
• Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning (2019) — 302 citations
• Solving Inverse Problems in Medical Imaging with Score-Based Generative Models (2021) — 774 citations
• NeRP: Implicit Neural Representation Learning with Prior Embedding for Sparsely Sampled Image Reconstruction (2021) — 316 citations