Search Results for author: Zonghan Wu

Found 8 papers, 6 papers with code

Personalized Federated Learning With Graph

1 code implementation2 Mar 2022 Fengwen Chen, Guodong Long, Zonghan Wu, Tianyi Zhou, Jing Jiang

We propose a novel structured federated learning (SFL) framework to learn both the global and personalized models simultaneously using client-wise relation graphs and clients' private data.

Personalized Federated Learning

Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting

no code implementations25 Nov 2021 Chuanpan Zheng, Xiaoliang Fan, Shirui Pan, Zonghan Wu, Cheng Wang, Philip S. Yu

In such a graph, the correlations between different nodes at different time steps are not explicitly reflected, which may restrict the learning ability of graph neural networks.

ConTIG: Continuous Representation Learning on Temporal Interaction Graphs

no code implementations27 Sep 2021 Xu Yan, Xiaoliang Fan, Peizhen Yang, Zonghan Wu, Shirui Pan, Longbiao Chen, Yu Zang, Cheng Wang

Representation learning on temporal interaction graphs (TIG) is to model complex networks with the dynamic evolution of interactions arising in a broad spectrum of problems.

Link Prediction Node Classification +1

TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting

1 code implementation25 Aug 2021 Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis

This paper aims to unify spatial dependency and temporal dependency in a non-Euclidean space while capturing the inner spatial-temporal dependencies for traffic data.

Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

2 code implementations24 May 2020 Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang

Modeling multivariate time series has long been a subject that has attracted researchers from a diverse range of fields including economics, finance, and traffic.

Graph Learning Multivariate Time Series Forecasting +1

Graph WaveNet for Deep Spatial-Temporal Graph Modeling

7 code implementations31 May 2019 Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang

Spatial-temporal graph modeling is an important task to analyze the spatial relations and temporal trends of components in a system.

Temporal Sequences Traffic Prediction

A Comprehensive Survey on Graph Neural Networks

5 code implementations3 Jan 2019 Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu

In this survey, we provide a comprehensive overview of graph neural networks (GNNs) in data mining and machine learning fields.

BIG-bench Machine Learning Image Classification +2

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