IEEE

Graph Filters for Signal Processing and Machine Learning on Graphs

Abstract: Filters are fundamental in extracting information from data. For time series and image data that reside on Euclidean domains, filters are the crux of many signal processing and machine ...
IEEE

GraphGST: Graph Generative Structure-Aware Transformer for Hyperspectral Image Classification

Abstract: Transformer holds significance in deep learning (DL) research. Node embedding (NE) and positional encoding (PE) are usually two indispensable components in a Transformer. The former can ...
GitHub

GraphStorm: Enterprise graph machine learning framework for billion-scale graphs

GraphStorm is an enterprise-grade graph machine learning (GML) framework designed for scalability and ease of use. It simplifies the development and deployment of GML models on industry-scale graphs ...
GitHub

GraphGPT: Graph Instruction Tuning for Large Language Models

Data Intelligence Lab@University of Hong Kong, Baidu Inc. This repository hosts the code, data and model weight of GraphGPT (SIGIR'24 full paper track). Due to compatibility issues, if you are using ...