Guangyin Jin

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 44 citations into it
• Building and Construction — 44 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it
• Graph Learning — 10 citations into it

Whom Guangyin Jin trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Ilya Sutskever
6. Alex Krizhevsky
7. Thomas Kipf
8. Karen Simonyan
9. Max Welling
10. Yann LeCun

Who trusts Guangyin Jin overall

1. Ming Jin

Papers from Guangyin Jin's perspective

Ordered by how strongly the researchers Guangyin Jin 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey (2023) — 520 citations
• Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution (2021) — 668 citations