Sina Lin

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 29 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 14 citations into it; #13,068 of 21,575 by trust here, #15,955 by citations
• Artificial Intelligence — 11 citations into it; #21,013 of 35,345 by trust here, #24,417 by citations
• Model Architectures — 5 citations into it

Whom Sina Lin trusts overall

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

1. Alex Krizhevsky
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Jia Deng
5. Ilya Sutskever
6. Andrew Zisserman
7. Kaiming He
8. Ross B. Girshick
9. Yoshua Bengio
10. Yann LeCun

Who trusts Sina Lin overall

1. Matei A. Zaharia
2. Minjie Wang
3. Chien-chin Huang
4. Linghao Song
5. Zhen Zhang
6. A. Aiken
7. Noam Shazeer
8. Wei Zeng
9. Jinyang Li
10. Fan Chen

Papers from Sina Lin's perspective

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

Their papers

• Exploring Hidden Dimensions in Parallelizing Convolutional Neural Networks (2018) — 131 citations
• Improving the Accuracy, Scalability, and Performance of Graph Neural Networks with Roc (2020) — 290 citations
• Exploring the Hidden Dimension in Accelerating Convolutional Neural Networks (2018) — 11 citations