most citedEpiGNN: Exploring Spatial Transmission with Graph Neural Network for Regional Epidemic Forecasting

2 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20232 cited

Improving Knowledge Graph Entity Alignment with Graph Augmentation

Feng Xie, Xiang Zeng, Bin Zhou +1

Entity alignment (EA) which links equivalent entities across different knowledge graphs (KGs) plays a crucial role in knowledge fusion. In recent years, graph neural networks (GNNs…

cs.RO2023

Multi-Arm Robot Task Planning for Fruit Harvesting Using Multi-Agent Reinforcement Learning

Tao Li, Feng Xie, Ya Xiong +1

The emergence of harvesting robotics offers a promising solution to the issue of limited agricultural labor resources and the increasing demand for fruits. Despite notable advancem…

q-bio.QM20222 cited

EpiGNN: Exploring Spatial Transmission with Graph Neural Network for Regional Epidemic Forecasting

Feng Xie, Zhong Zhang, Liang Li +2

Epidemic forecasting is the key to effective control of epidemic transmission and helps the world mitigate the crisis that threatens public health. To better understand the transmi…

cs.LG2022

Inter- and Intra-Series Embeddings Fusion Network for Epidemiological Forecasting

Feng Xie, Zhong Zhang, Xuechen Zhao +2

The accurate forecasting of infectious epidemic diseases is the key to effective control of the epidemic situation in a region. Most existing methods ignore potential dynamic depen…

math.AP20221 cited

Long time well-posedness of compressible magnetohydrodynamics boundary layer equations in Sobolev space

Shengxin Li, Feng Xie

In this paper we consider the long time well-posedness of solutions to two dimensional compressible magnetohydrodynamics (MHD) boundary layer equations. When the initial data is a…