Jindong Han

Orcid: 0000-0002-1542-6149

Affiliations:
  • Hong Kong University of Science and Technology, China
  • Baidu Research, Beijing, China (former)
  • Beijing University of Posts and Telecommunications, China (former)


According to our database1, Jindong Han authored at least 26 papers between 2018 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
BigST: Linear Complexity Spatio-Temporal Graph Neural Network for Traffic Forecasting on Large-Scale Road Networks.
Proc. VLDB Endow., January, 2024

A Prompt-Guided Spatio-Temporal Transformer Model for National-Wide Nuclear Radiation Forecasting.
CoRR, 2024

Meta-Transfer Learning Empowered Temporal Graph Networks for Cross-City Real Estate Appraisal.
CoRR, 2024

Erase then Rectify: A Training-Free Parameter Editing Approach for Cost-Effective Graph Unlearning.
CoRR, 2024

GraphLoRA: Structure-Aware Contrastive Low-Rank Adaptation for Cross-Graph Transfer Learning.
CoRR, 2024

Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction.
CoRR, 2024

Empowering Pre-Trained Language Models for Spatio-Temporal Forecasting via Decoupling Enhanced Discrete Reprogramming.
CoRR, 2024

Simplified Mamba with Disentangled Dependency Encoding for Long-Term Time Series Forecasting.
CoRR, 2024

Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models.
CoRR, 2024

Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Urban Foundation Models: A Survey.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023
Kill Two Birds With One Stone: A Multi-View Multi-Adversarial Learning Approach for Joint Air Quality and Weather Prediction.
IEEE Trans. Knowl. Data Eng., November, 2023

Semi-Supervised Air Quality Forecasting via Self-Supervised Hierarchical Graph Neural Network.
IEEE Trans. Knowl. Data Eng., May, 2023

Unified route representation learning for multi-modal transportation recommendation with spatiotemporal pre-training.
VLDB J., March, 2023

Machine Learning for Urban Air Quality Analytics: A Survey.
CoRR, 2023

Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Network.
CoRR, 2023

Cross-City Traffic Prediction via Semantic-Fused Hierarchical Graph Transfer Learning.
CoRR, 2023

iETA: A Robust and Scalable Incremental Learning Framework for Time-of-Arrival Estimation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
Incorporating Multi-Source Urban Data for Personalized and Context-Aware Multi-Modal Transportation Recommendation.
IEEE Trans. Knowl. Data Eng., 2022

Multi-Agent Graph Convolutional Reinforcement Learning for Dynamic Electric Vehicle Charging Pricing.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Adversarial Transfer Learning for Deep Learning Based Automatic Modulation Classification.
IEEE Signal Process. Lett., 2020

Multi-Modal Transportation Recommendation with Unified Route Representation Learning.
Proc. VLDB Endow., 2020

2019
GraphConvLSTM: Spatiotemporal Learning for Activity Recognition with Wearable Sensors.
Proceedings of the 2019 IEEE Global Communications Conference, 2019

2018
HAR-Net: Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition.
CoRR, 2018


  Loading...