GitHub

A PyTorch implementation of Signed Graph Convolutional Network (ICDM 2018).

--edge-path STR Input graph path. Default is `input/bitcoin_otc.csv`. --features-path STR Features path. Default is `input/bitcoin_otc.csv`. --embedding-path STR ...
GitHub

Graph Markov Network for Traffic Forecasting with Missing Data

This is the github repo for sharing the code for implementing the Graph Markov Network (GMN) proposed in [1]. The GMN is proposed to solve the traffic forecasting problems while the traffic data has ...
IEEE

Probabilistic analysis of the network reliability problem on a random graph ensemble

Abstract: In the field of computer science, the network reliability problem for evaluating the network failure probability has been extensively investigated. For a given undirected graph G, the ...
Frontiers

Extracting default mode network based on graph neural network for resting state fMRI study

Functional magnetic resonance imaging (fMRI)-based study of functional connections in the brain has been highlighted by numerous human and animal studies recently, which have provided significant ...
IEEE

Multi-layer Graph Neural Network-Based Random Anomalous Behavior Detection

Abstract: Random anomalous behavior is a false or redundant behavior that randomly appears in the network structure, affecting the analysis result of the network. Current methods mainly capture the ...
Frontiers

MoGCN: A Multi-Omics Integration Method Based on Graph Convolutional Network for Cancer Subtype Analysis

In light of the rapid accumulation of large-scale omics datasets, numerous studies have attempted to characterize the molecular and clinical features of cancers from a multi-omics perspective. However ...
Visual Studio Magazine

Neural Network L2 Regularization Using Python

Our data science expert continues his exploration of neural network programming, explaining how regularization addresses the problem of model overfitting, caused by network overtraining. Neural ...