Shengnan Guo
Orcid: 0000-0002-3008-4511Affiliations:
- Beijing Jiaotong University, School of Computer and Information Technology, Beijing Key Laboratory of Traffic Data Analysis and Mining, China
According to our database1,
Shengnan Guo
authored at least 26 papers
between 2019 and 2024.
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Bibliography
2024
Spatial-temporal uncertainty-aware graph networks for promoting accuracy and reliability of traffic forecastin.
Expert Syst. Appl., March, 2024
Diff-RNTraj: A Structure-aware Diffusion Model for Road Network-constrained Trajectory Generation.
CoRR, 2024
CoRR, 2024
2023
Proc. ACM Manag. Data, September, 2023
Enough Waiting for the Couriers: Learning to Estimate Package Pick-up Arrival Time from Couriers' Spatial-Temporal Behaviors.
ACM Trans. Intell. Syst. Technol., 2023
A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospects.
CoRR, 2023
Generative-Contrastive-Attentive Spatial-Temporal Network for Traffic Data Imputation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023
WITRAN: Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
M<sup>2</sup>G4RTP: A Multi-Level and Multi-Task Graph Model for Instant-Logistics Route and Time Joint Prediction.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023
Self-Supervised Spatial-Temporal Bottleneck Attentive Network for Efficient Long-term Traffic Forecasting.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023
GMDNet: A Graph-Based Mixture Density Network for Estimating Packages' Multimodal Travel Time Distribution.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Contrastive Pre-training with Adversarial Perturbations for Check-In Sequence Representation Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
IEEE Trans. Knowl. Data Eng., 2022
Learning Dynamics and Heterogeneity of Spatial-Temporal Graph Data for Traffic Forecasting.
IEEE Trans. Knowl. Data Eng., 2022
DeepRoute+: Modeling Couriers' Spatial-temporal Behaviors and Decision Preferences for Package Pick-up Route Prediction.
ACM Trans. Intell. Syst. Technol., 2022
Building and exploiting spatial-temporal knowledge graph for next POI recommendation.
Knowl. Based Syst., 2022
2021
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021
GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Knowl. Based Syst., 2020
Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
IEEE Trans. Intell. Transp. Syst., 2019
基于时空循环卷积网络的城市区域人口流量预测 (Citywide Crowd Flows Prediction Based on Spatio-Temporal Recurrent Convolutional Networks).
计算机科学, 2019
Learning Time-Aware Distributed Representations of Locations from Spatio-Temporal Trajectories.
Proceedings of the Database Systems for Advanced Applications, 2019
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019