GitHub

Graph Neural Prompting with Large Language Models

Large language models (LLMs) have shown remarkable generalization capability with exceptional performance in various language modeling tasks. However, they still exhibit inherent limitations in ...
GitHub

Learning Graph Representation via Graph Entropy Maximization (GeMax)

This is the code repository for [Paper]: "Learning Graph Representation via Graph Entropy Maximization (ICML 2024)". GeMax is an approximation method leveraging orthonormal representation for graph ...
IEEE

AutoDDI: Drug–Drug Interaction Prediction With Automated Graph Neural Network

Abstract: Drug–drug interaction (DDI) has attracted widespread attention because when incompatible drugs are taken together, DDI will lead to adverse effects on the body, such as drug poisoning or ...
IEEE

Graph Oriented Attention Networks

Abstract: Graph Attention Networks (GAT) is a type of neural network architecture designed to effectively model and process data represented as graphs. GATs leverage the concept of attention ...