Hua Wei

Control and Systems Engineering · AAAI Conference on Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 6 papers; trusts 19 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Control and Systems Engineering — 45 citations into it; #2,790 of 8,257 by trust here, #2,295 by citations
• Building and Construction — 42 citations into it; #629 of 2,909 by trust here, #824 by citations
• Transportation — 36 citations into it
• Reinforcement Learning — 15 citations into it
• Computer Networks and Communications — 9 citations into it
• Automotive Engineering — 6 citations into it; #1,404 of 3,081 by trust here, #1,686 by citations
• Molecular Biology — 6 citations into it
• Management Information Systems — 5 citations into it

Whom Hua Wei trusts overall

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

1. Marco A. Wiering
2. Pravin Pratap Varaiya
3. van der D David Pol
4. Richard S. Sutton
5. Baher Abdulhai
6. Guanjie Zheng
7. James S. Albus
8. Lior Kuyer
9. Samah El-Tantawy
10. Huichu Zhang

Who trusts Hua Wei overall

1. Chacha Chen
2. Saeed Rahmani
3. Guanjie Zheng
4. Nan Xu
5. Asiye Baghbani
6. Zhi Zhang
7. Cathy Wu
8. Afshin Oroojlooyjadid
9. Zhuangdi Zhu
10. Huichu Zhang

Papers from Hua Wei's perspective

Ordered by how strongly the researchers Hua Wei trusts endorse each paper. Same corpus, a different order for every researcher.

1. Long Short-Term Memory
2. Attention is All you Need (Neural Information Processing Systems)
3. Gradient-based learning applied to document recognition
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet classification with deep convolutional neural networks
7. Human-level control through deep reinforcement learning
8. Reinforcement Learning: An Introduction
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Toward A Thousand Lights: Decentralized Deep Reinforcement Learning for Large-Scale Traffic Signal Control (2020) — 480 citations
• CoLight: Learning Network-level Cooperation for Traffic Signal Control (2019) — 527 citations
• PressLight: Learning Max Pressure Control to Coordinate Traffic Signals in Arterial Network (2019) — 485 citations
• A Survey on Traffic Signal Control Methods (2019) — 297 citations
• IntelliLight: A Reinforcement Learning Approach for Intelligent Traffic Light Control (2018) — 771 citations
• Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction (2018) — 833 citations