12 citations · 21 across the 25 of their papers we have counts for
19 papers · 1 filter
Enhancing Multivariate Time Series Forecasting with Global Temporal Retrieval
Fanpu Cao, Lu Dai, Jindong Han +1
Multivariate time series forecasting (MTSF) plays a vital role in numerous real-world applications, yet existing models remain constrained by their reliance on a limited historical…
MixTTE: Multi-Level Mixture-of-Experts for Scalable and Adaptive Travel Time Estimation
Wenzhao Jiang, Jindong Han, Ruiqian Han +1
Accurate Travel Time Estimation (TTE) is critical for ride-hailing platforms, where errors directly impact user experience and operational efficiency. While existing production sys…
DAMBench: A Multi-Modal Benchmark for Deep Learning-based Atmospheric Data Assimilation
Hao Wang, Zixuan Weng, Jindong Han +2
Data Assimilation is a cornerstone of atmospheric system modeling, tasked with reconstructing system states by integrating sparse, noisy observations with prior estimation. While t…
Foundation Models for Scientific Discovery: From Paradigm Enhancement to Paradigm Transition
Fan Liu, Jindong Han, Tengfei Lyu +5
Foundation models (FMs), such as GPT-4 and AlphaFold, are reshaping the landscape of scientific research. Beyond accelerating tasks such as hypothesis generation, experimental desi…
PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems
Hao Wang, Jindong Han, Wei Fan +2
Data Assimilation (DA) plays a critical role in atmospheric science by reconstructing spatially continous estimates of the system state, which serves as initial conditions for scie…
Unsupervised Graph Anomaly Detection via Multi-Hypersphere Heterophilic Graph Learning
Hang Ni, Jindong Han, Nengjun Zhu +1
Graph Anomaly Detection (GAD) plays a vital role in various data mining applications such as e-commerce fraud prevention and malicious user detection. Recently, Graph Neural Networ…
NRFormer: Nationwide Nuclear Radiation Forecasting with Spatio-Temporal Transformer
Tengfei Lyu, Jindong Han, Hao Liu
Nuclear radiation, which refers to the energy emitted from atomic nuclei during decay, poses significant risks to human health and environmental safety. Recently, advancements in m…
Meta-Transfer Learning Powered Temporal Graph Networks for Cross-City Real Estate Appraisal
Weijia Zhang, Jindong Han, Hao Liu +3
Real estate appraisal is important for a variety of endeavors such as real estate deals, investment analysis, and real property taxation. Recently, deep learning has shown great pr…
Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction
Ziyang Wu, Fan Liu, Jindong Han +2
As various types of crime continue to threaten public safety and economic development, predicting the occurrence of multiple types of crimes becomes increasingly vital for effectiv…
Erase then Rectify: A Training-Free Parameter Editing Approach for Cost-Effective Graph Unlearning
Zhe-Rui Yang, Jindong Han, Chang-Dong Wang +1
Graph unlearning, which aims to eliminate the influence of specific nodes, edges, or attributes from a trained Graph Neural Network (GNN), is essential in applications where privac…
GraphLoRA: Structure-Aware Contrastive Low-Rank Adaptation for Cross-Graph Transfer Learning
Zhe-Rui Yang, Jindong Han, Chang-Dong Wang +1
Graph Neural Networks (GNNs) have demonstrated remarkable proficiency in handling a range of graph analytical tasks across various domains, such as e-commerce and social networks.…
RePST: Language Model Empowered Spatio-Temporal Forecasting via Semantic-Oriented Reprogramming
Hao Wang, Jindong Han, Wei Fan +2
Spatio-temporal forecasting is pivotal in numerous real-world applications, including transportation planning, energy management, and climate monitoring. In this work, we aim to ha…
SDE: A Simplified and Disentangled Dependency Encoding Framework for State Space Models in Time Series Forecasting
Zixuan Weng, Jindong Han, Wenzhao Jiang +1
In recent years, advancements in deep learning have spurred the development of numerous models for Long-term Time Series Forecasting (LTSF). However, most existing approaches strug…
Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction
Wenzhao Jiang, Jindong Han, Hao Liu +3
Rapid urbanization has significantly escalated traffic congestion, underscoring the need for advanced congestion prediction services to bolster intelligent transportation systems.…
Machine Learning for Urban Air Quality Analytics: A Survey
Jindong Han, Weijia Zhang, Hao Liu +1
The increasing air pollution poses an urgent global concern with far-reaching consequences, such as premature mortality and reduced crop yield, which significantly impact various a…
Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Network
Weijia Zhang, Le Zhang, Jindong Han +5
Accurate traffic forecasting is crucial for the development of Intelligent Transportation Systems (ITS), playing a pivotal role in modern urban traffic management. Traditional fore…
Semantic-Fused Multi-Granularity Cross-City Traffic Prediction
Kehua Chen, Yuxuan Liang, Jindong Han +3
Accurate traffic prediction is essential for effective urban management and the improvement of transportation efficiency. Recently, data-driven traffic prediction methods have been…
Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks
Jindong Han, Hao Liu, Hengshu Zhu +2
Accurate and timely air quality and weather predictions are of great importance to urban governance and human livelihood. Though many efforts have been made for air quality or weat…
HAR-Net:Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition
Mingtao Dong, Jindong Han
Wearable computing and context awareness are the focuses of study in the field of artificial intelligence recently. One of the most appealing as well as challenging applications is…