Guangyin Jin

Orcid: 0000-0002-9837-6836

According to our database¹, Guangyin Jin authored at least 31 papers between 2018 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospects.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., December, 2024

Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., October, 2024

Spatio-temporal Dual Graph Neural Networks for Travel Time Estimation.

[BibT_eX]

[DOI]

ACM Trans. Spatial Algorithms Syst., September, 2024

Dynamic multi-scale spatial-temporal graph convolutional network for traffic flow prediction.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2024

Non-informative noise-enhanced stochastic neural networks for improving adversarial robustness.

[BibT_eX]

[DOI]

Inf. Fusion, 2024

2023

Automated Dilated Spatio-Temporal Synchronous Graph Modeling for Traffic Prediction.

[BibT_eX]

[DOI]

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

Dual Graph Convolution Architecture Search for Travel Time Estimation.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., August, 2023

A spatiotemporal graph generative adversarial networks for short-term passenger flow prediction in urban rail transit systems.

[BibT_eX]

[DOI]

Int. J. Gen. Syst., August, 2023

Urban hotspot forecasting via automated spatio-temporal information fusion.

[BibT_eX]

[DOI]

Appl. Soft Comput., March, 2023

Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, January, 2023

Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis.

[BibT_eX]

[DOI]

CoRR, 2023

HUTFormer: Hierarchical U-Net Transformer for Long-Term Traffic Forecasting.

[BibT_eX]

[DOI]

CoRR, 2023

Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey.

[BibT_eX]

[DOI]

CoRR, 2023

Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Network-Wide Link Travel Time and Station Waiting Time Estimation Using Automatic Fare Collection Data: A Computational Graph Approach.

[BibT_eX]

[DOI]

IEEE Trans. Intell. Transp. Syst., 2022

Adaptive Dual-View WaveNet for urban spatial-temporal event prediction.

[BibT_eX]

[DOI]

Inf. Sci., 2022

Deep multi-view graph-based network for citywide ride-hailing demand prediction.

[BibT_eX]

[DOI]

Neurocomputing, 2022

STGNN-TTE: Travel time estimation via spatial-temporal graph neural network.

[BibT_eX]

[DOI]

Future Gener. Comput. Syst., 2022

Jointly Modeling Intersections and Road Segments for Travel Time Estimation via Dual Graph Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the Spatial Data and Intelligence - Third International Conference, 2022

Automated Spatio-Temporal Synchronous Modeling with Multiple Graphs for Traffic Prediction.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

GSEN: An ensemble deep learning benchmark model for urban hotspots spatiotemporal prediction.

[BibT_eX]

[DOI]

Neurocomputing, 2021

Spatial-Temporal Dual Graph Neural Networks for Travel Time Estimation.

[BibT_eX]

[DOI]

CoRR, 2021

Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution.

[BibT_eX]

[DOI]

CoRR, 2021

A Deep Urban Hotspots Prediction Framework with Modeling Geography-Semantic Dynamics.

[BibT_eX]

[DOI]

Proceedings of the Spatial Data and Intelligence - Second International Conference, 2021

Hierarchical Neural Architecture Search for Travel Time Estimation.

[BibT_eX]

[DOI]

Proceedings of the SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, 2021

2020

CSAN: A neural network benchmark model for crime forecasting in spatio-temporal scale.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2020

Deep Multi-View Spatiotemporal Virtual Graph Neural Network for Significant Citywide Ride-hailing Demand Prediction.

[BibT_eX]

[DOI]

CoRR, 2020

Urban Fire Situation Forecasting: Deep sequence learning with spatio-temporal dynamics.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2020

SDPN: A Neural Network Approach for E-hailing Car Supply and Demand Prediction.

[BibT_eX]

[DOI]

Proceedings of the BDET 2020: 2nd International Conference on Big Data Engineering and Technology, 2020

2019

Crime-GAN: A Context-based Sequence Generative Network for Crime Forecasting with Adversarial Loss.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Addressing the Task of Rocket Recycling with Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Information Technology: IoT and Smart City, 2018

Guangyin Jin

Timeline

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