18 citations · 89 across the 20 of their papers we have counts for
20 papers
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…
Spatial Heterophily Aware Graph Neural Networks
Congxi Xiao, Jingbo Zhou, Jizhou Huang +2
Graph Neural Networks (GNNs) have been broadly applied in many urban applications upon formulating a city as an urban graph whose nodes are urban objects like regions or points of…
Multi-Temporal Relationship Inference in Urban Areas
Shuangli Li, Jingbo Zhou, Ji Liu +3
Finding multiple temporal relationships among locations can benefit a bunch of urban applications, such as dynamic offline advertising and smart public transport planning. While so…
Towards Table-to-Text Generation with Pretrained Language Model: A Table Structure Understanding and Text Deliberating Approach
Miao Chen, Xinjiang Lu, Tong Xu +4
Although remarkable progress on the neural table-to-text methods has been made, the generalization issues hinder the applicability of these models due to the limited source tables.…
A Contextual Master-Slave Framework on Urban Region Graph for Urban Village Detection
Congxi Xiao, Jingbo Zhou, Jizhou Huang +4
Urban villages (UVs) refer to the underdeveloped informal settlement falling behind the rapid urbanization in a city. Since there are high levels of social inequality and social ri…
Multi-Job Intelligent Scheduling with Cross-Device Federated Learning
Ji Liu, Juncheng Jia, Beichen Ma +5
Recent years have witnessed a large amount of decentralized data in various (edge) devices of end-users, while the decentralized data aggregation remains complicated for machine le…
Data Placement for Multi-Tenant Data Federation on the Cloud
Ji Liu, Lei Mo, Sijia Yang +4
Due to privacy concerns of users and law enforcement in data security and privacy, it becomes more and more difficult to share data among organizations. Data federation brings new…
Efficient Device Scheduling with Multi-Job Federated Learning
Chendi Zhou, Ji Liu, Juncheng Jia +4
Recent years have witnessed a large amount of decentralized data in multiple (edge) devices of end-users, while the aggregation of the decentralized data remains difficult for mach…
Adversarial Neural Trip Recommendation
Linlang Jiang, Jingbo Zhou, Tong Xu +4
Trip recommender system, which targets at recommending a trip consisting of several ordered Points of Interest (POIs), has long been treated as an important application for many lo…
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction
Shuangli Li, Jingbo Zhou, Tong Xu +2
Recently many efforts have been devoted to applying graph neural networks (GNNs) to molecular property prediction which is a fundamental task for computational drug and material di…
Structure-aware Interactive Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinity
Shuangli Li, Jingbo Zhou, Tong Xu +6
Drug discovery often relies on the successful prediction of protein-ligand binding affinity. Recent advances have shown great promise in applying graph neural networks (GNNs) for b…
Spatial Object Recommendation with Hints: When Spatial Granularity Matters
Hui Luo, Jingbo Zhou, Zhifeng Bao +5
Existing spatial object recommendation algorithms generally treat objects identically when ranking them. However, spatial objects often cover different levels of spatial granularit…
Distance-aware Molecule Graph Attention Network for Drug-Target Binding Affinity Prediction
Jingbo Zhou, Shuangli Li, Liang Huang +5
Accurately predicting the binding affinity between drugs and proteins is an essential step for computational drug discovery. Since graph neural networks (GNNs) have demonstrated re…
C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak
Congxi Xiao, Jingbo Zhou, Jizhou Huang +4
The novel coronavirus disease (COVID-19) has crushed daily routines and is still rampaging through the world. Existing solution for nonpharmaceutical interventions usually needs to…
Intelligent Exploration for User Interface Modules of Mobile App with Collective Learning
Jingbo Zhou, Zhenwei Tang, Min Zhao +6
A mobile app interface usually consists of a set of user interface modules. How to properly design these user interface modules is vital to achieving user satisfaction for a mobile…
Defending Water Treatment Networks: Exploiting Spatio-temporal Effects for Cyber Attack Detection
Dongjie Wang, Pengyang Wang, Jingbo Zhou +3
While Water Treatment Networks (WTNs) are critical infrastructures for local communities and public health, WTNs are vulnerable to cyber attacks. Effective detection of attacks can…
Polestar: An Intelligent, Efficient and National-Wide Public Transportation Routing Engine
Hao Liu, Ying Li, Yanjie Fu +4
Public transportation plays a critical role in people's daily life. It has been proven that public transportation is more environmentally sustainable, efficient, and economical tha…
Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction
Weijia Zhang, Hao Liu, Yanchi Liu +2
The ability to predict city-wide parking availability is crucial for the successful development of Parking Guidance and Information (PGI) systems. Indeed, the effective prediction…
Store Location Selection via Mining Search Query Logs of Baidu Maps
Mengwen Xu, Tianyi Wang, Zhengwei Wu +3
Choosing a good location when opening a new store is crucial for the future success of a business. Traditional methods include offline manual survey, which is very time consuming,…
Early Warning of Human Crowds Based on Query Data from Baidu Map: Analysis Based on Shanghai Stampede
Jingbo Zhou, Hongbin Pei, Haishan Wu
Without sufficient preparation and on-site management, the mass scale unexpected huge human crowd is a serious threat to public safety. A recent impressive tragedy is the 2014 Shan…