149 citations · 272 across the 8 of their papers we have counts for
8 papers
Are GNNs Actually Effective for Multimodal Fault Diagnosis in Microservice Systems?
Fei Gao, Ruyue Xin, Xiaocui Li +1
Graph Neural Networks (GNNs) are widely adopted for fault diagnosis in microservice systems, premised on their ability to model service dependencies. However, the necessity of expl…
Recurrent Dynamic Message Passing with Loops for Epidemics on Networks
Fei Gao, Jing Liu, Yaqian Zhao
Several theoretical methods have been developed to approximate prevalence and threshold of epidemics on networks. Among them, the recurrent dynamic message-passing (rDMP) theory of…
Expectation-Maximizing Network Reconstruction and MostApplicable Network Types Based on Binary Time Series Data
Kaiwei Liu, Xing Lv, Fei Gao +1
Based on the binary time series data of social infection dynamics, we propose a general framework to reconstruct 2-simplex complexes with two-body and three-body interactions by co…
NEDMP: Neural Enhanced Dynamic Message Passing
Fei Gao, Yan Zhang, Jiang Zhang
Predicting stochastic spreading processes on complex networks is critical in epidemic control, opinion propagation, and viral marketing. We focus on the problem of inferring the ti…
TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data
Lun Du, Fei Gao, Xu Chen +5
Tabular data are ubiquitous for the widespread applications of tables and hence have attracted the attention of researchers to extract underlying information. One of the critical p…
Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective
Lun Du, Xu Chen, Fei Gao +4
Network Embedding aims to learn a function mapping the nodes to Euclidean space contribute to multiple learning analysis tasks on networks. However, the noisy information behind th…
PM2.5-GNN: A Domain Knowledge Enhanced Graph Neural Network For PM2.5 Forecasting
Shuo Wang, Yanran Li, Jiang Zhang +3
When predicting PM2.5 concentrations, it is necessary to consider complex information sources since the concentrations are influenced by various factors within a long period. In th…
Gumbel-softmax Optimization: A Simple General Framework for Combinatorial Optimization Problems on Graphs
Jing Liu, Fei Gao, Jiang Zhang
Many problems in real life can be converted to combinatorial optimization problems (COPs) on graphs, that is to find a best node state configuration or a network structure such tha…