Jun Li

According to our database, Jun Li authored at least 12 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Multimodal end-to-end autonomous driving via bilateral modality interaction.

Ze Yu, Jun Li, Zesong Chen, Yuzhen Wei, Xiaofei Zhang, Xiaojun Tan

Expert Syst. Appl., 2025

GLformer: Global-local spatio-temporal graph fusion transformer network for traffic flow prediction.

Kunxiang Deng, Xinyu Zhang, Haoxuan Kuang, Kemal Polat, Fayadh Alenezi, Jun Li

Appl. Soft Comput., 2025

Deep meta-learning approach for regional parking occupancy prediction considering heterogeneous and real-time information.

Haoxuan Kuang, Kunxiang Deng, Qiuxuan Wang, Wei Ye, Haohao Qu, Jun Li

Adv. Eng. Informatics, 2025

2024

A Physics-Informed and Attention-Based Graph Learning Approach for Regional Electric Vehicle Charging Demand Prediction.

Haohao Qu, Haoxuan Kuang, Qiuxuan Wang, Jun Li, Linlin You

IEEE Trans. Intell. Transp. Syst., October, 2024

Attention-based Citywide Electric Vehicle Charging Demand Prediction Approach Considering Urban Region and Dynamic Influences.

Haoxuan Kuang, Kunxiang Deng, Linlin You, Jun Li

CoRR, 2024

Multimodal joint prediction of traffic spatial-temporal data with graph sparse attention mechanism and bidirectional temporal convolutional network.

Dongran Zhang, Jiangnan Yan, Kemal Polat, Adi Alhudhaif, Jun Li

Adv. Eng. Informatics, 2024

2023

An Integrated Approach for the Near Real-Time Parking Occupancy Prediction.

Jun Li, Haohao Qu, Linlin You

IEEE Trans. Intell. Transp. Syst., April, 2023

Trajectory Generation of Ultra-Low-Frequency Travel Routes in Large-Scale Complex Road Networks.

Jun Li, Wenting Zhao

Syst., February, 2023

A physics-informed and attention-based graph learning approach for regional electric vehicle charging demand prediction.

Haohao Qu, Haoxuan Kuang, Jun Li, Linlin You

CoRR, 2023

Traffic Spatial-Temporal Prediction Based on Neural Architecture Search.

Dongran Zhang, Gang Luo, Jun Li

Proceedings of the 18th International Symposium on Spatial and Temporal Data, 2023

PI-Parking: A Physics Informed Neural Network Approach for Parking Availability Prediction.

Yijun Dong, Haoxuan Kuang, Jun Li

Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems, 2023

2022

Improving Parking Occupancy Prediction in Poor Data Conditions Through Customization and Learning to Learn.

Haohao Qu, Sheng Liu, Zihan Guo, Linlin You, Jun Li

Proceedings of the Knowledge Science, Engineering and Management, 2022