Zezhi Shao

Artificial Intelligence · 2022–2023

A researcher in the Science corpus: 4 papers; trusts 69 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 71 citations into it
• Building and Construction — 62 citations into it
• Transportation — 48 citations into it
• Signal Processing — 32 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Model Architectures — 25 citations into it
• Graph Learning — 19 citations into it
• Control and Systems Engineering — 15 citations into it

Whom Zezhi Shao trusts overall

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

1. Zonghan Wu
2. Ilya Sutskever
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Kaiming He
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Shengna Guo
9. Kyunghyun Cho
10. Yann LeCun

Who trusts Zezhi Shao overall

1. Guangyin Jin
2. Ming Jin
3. Yuxuan Liang

Papers from Zezhi Shao's perspective

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

Their papers

• Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting (2022) — 370 citations
• Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey (2023) — 520 citations
• Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting (2022) — 482 citations
• Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting (2022) — 378 citations