Qiang Wu

Orcid: 0000-0003-0655-0479

Affiliations:
  • University of Electronic Science and Technology of China, Chengdu, China
  • Lanzhou University, School of Information and Engineering, China (PhD 2020)


According to our database1, Qiang Wu authored at least 21 papers between 2019 and 2024.

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Timeline

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Bibliography

2024
Influential simplices mining via simplicial convolutional networks.
Inf. Process. Manag., 2024

DST-GTN: Dynamic Spatio-Temporal Graph Transformer Network for Traffic Forecasting.
CoRR, 2024

Higher-Order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Cooperative Network Learning for Large-Scale and Decentralized Graphs.
CoRR, 2023

Influential Simplices Mining via Simplicial Convolutional Network.
CoRR, 2023

TransformerLight: A Novel Sequence Modeling Based Traffic Signaling Mechanism via Gated Transformer.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
The Bounds of Improvements Toward Real-Time Forecast of Multi-Scenario Train Delays.
IEEE Trans. Intell. Transp. Syst., 2022

Distributed agent-based deep reinforcement learning for large scale traffic signal control.
Knowl. Based Syst., 2022

Entity knowledge transfer-oriented dual-target cross-domain recommendations.
Expert Syst. Appl., 2022

DynamicLight: Dynamically Tuning Traffic Signal Duration with DRL.
CoRR, 2022

Knowledge intensive state design for traffic signal control.
CoRR, 2022

Expression might be enough: representing pressure and demand for reinforcement learning based traffic signal control.
Proceedings of the International Conference on Machine Learning, 2022

2021
Expression is enough: Improving traffic signal control with advanced traffic state representation.
CoRR, 2021

Efficient Pressure: Improving efficiency for signalized intersections.
CoRR, 2021

ClothGAN: generation of fashionable Dunhuang clothes using generative adversarial networks.
Connect. Sci., 2021

Multi-agent deep reinforcement learning for traffic signal control with Nash Equilibrium.
Proceedings of the 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, 2021

Communicate with Traffic Lights and Vehicles Based on Multi-Agent Reinforcement Learning.
Proceedings of the 24th IEEE International Conference on Computer Supported Cooperative Work in Design, 2021

2020
An Edge Based Multi-Agent Auto Communication Method for Traffic Light Control.
Sensors, 2020

Towards Attention-Based Convolutional Long Short-Term Memory for Travel Time Prediction of Bus Journeys.
Sensors, 2020

An Efficient Tiny Feature Map Network for Real-Time Semantic Segmentation.
Proceedings of the Advances in Visual Computing - 15th International Symposium, 2020

2019
Smart fog based workflow for traffic control networks.
Future Gener. Comput. Syst., 2019


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