IEEE

Bidirectional Probabilistic Multi-Graph Learning and Decomposition for Multi-View Clustering

Abstract: Graph-based multi-view clustering has attracted remarkable attention due to its impressive performance. However, the typical framework consisting of graph learning and indicator generation ...
datanami.com

TigerGraph Serves Collaboration and Security with Multi-Graph

The capability to share data insights with other people or departments is instrumental to collaboration, and yet it’s also the source of real security concerns in today’s dangerous world. Graph ...
Frontiers

Multi-atlas ensemble graph neural network model for major depressive disorder detection using functional MRI data

Major depressive disorder (MDD) is one of the most common mental disorders, with significant impacts on many daily activities and quality of life. It stands as one of the most common mental disorders ...
Frontiers

A multi-graph convolutional network method for Alzheimer’s disease diagnosis based on multi-frequency EEG data with dual-mode connectivity

Objective: Alzheimer’s disease (AD) is mainly identified by cognitive function deterioration. Diagnosing AD at early stages poses significant challenges for both researchers and healthcare ...
GitHub

Multi-Task Graph Neural Network on ogbn-arxiv Dataset

In this repository, we present the design, training, and analysis of a Multi-Task Graph Neural Network (Multi-Task GNN) applied to the ogbn-arxiv dataset. Our goal is to evaluate the performance of ...
GitHub

This project dives into a graph knowledge base for information retrieval and examines the performances between a BM25+RRF+Reranker, Graph, and Multi Hop Graph RAG systems in ...

This repository contains a Streamlit application for running a Multi-Hop Retrieval-Augmented Generation (RAG) pipeline using graph-based reasoning. The app will allow uploading documents where it ...