Xinglei Wang

Orcid: 0000-0002-9824-7663

According to our database1, Xinglei Wang authored at least 14 papers between 2019 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Links

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Bibliography

2025
Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places.
CoRR, June, 2025

Multi-modal contrastive learning of urban space representations from POI data.
Comput. Environ. Urban Syst., 2025

Enriching Location Representation with Detailed Semantic Information.
Proceedings of the 13th International Conference on Geographic Information Science, 2025

2024
HSeq2Seq: Hierarchical graph neural network for accurate mobile traffic forecasting.
Inf. Sci., 2024

Multimodal Contrastive Learning of Urban Space Representations from POI Data.
CoRR, 2024

V-RoAst: A New Dataset for Visual Road Assessment.
CoRR, 2024

Zero-shot Building Age Classification from Facade Image Using GPT-4.
CoRR, 2024

2023
Where Would I Go Next? Large Language Models as Human Mobility Predictors.
CoRR, 2023

The Ups and Downs of London High Streets Throughout COVID-19 Pandemic: Insights from Footfall-Based Clustering Analysis (Short Paper).
Proceedings of the 12th International Conference on Geographic Information Science, 2023

Customer Profiling Based on Mobile Apps GPS Data : A Case Study on Westfield Shopping Malls.
Proceedings of the 2023 30th International Conference on Geoinformatics, 2023

2020
Forecast Network-Wide Traffic States for Multiple Steps Ahead: A Deep Learning Approach Considering Dynamic Non-Local Spatial Correlation and Non-Stationary Temporal Dependency.
CoRR, 2020

A Hybrid Deep Learning-Based Traffic Forecasting Approach Integrating Adjacency Filtering and Frequency Decomposition.
IEEE Access, 2020

2019
A Hybrid Traffic Speed Forecasting Approach Integrating Wavelet Transform and Motif-based Graph Convolutional Recurrent Neural Network.
CoRR, 2019

Wavelet-HST: A Wavelet-Based Higher-Order Spatio-Temporal Framework for Urban Traffic Speed Prediction.
IEEE Access, 2019


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