IEEE

Remaining Useful Life Prediction of Bearings Based on Graph Isomorphism Network with Graph-in-Graph Framework

Abstract: The graph neural networks (GNNs) have drawn much attention for predicting the remaining useful life (RUL) due to their excellent performance in processing correlation relationship among data ...
GitHub

Source code of our NeurIPS 2025 paper "Unifying and Enhancing Graph Transformers via a Hierarchical Mask Framework"

python==3.10.14 torch==2.3.1+cu121 --index-url https://download.pytorch.org/whl/cu121 ogb==1.3.6 torch-geometric==2.5.3 torch-scatter==2.1.2+pt23cu121 --index-url ...
IEEE

A Hierarchical Conflict Resolution Framework With Graph Transformer-Based Reinforcement Learning for Heterogeneous UAV Networks

Abstract: Dense unmanned aerial vehicle (UAV) networks comprising different types of UAVs have been widely applied across various domains, leading to potential conflicts within heterogeneous UAV ...
GitHub

great-wind/1517005260_graph-rag-agent

graph-rag-agent/ ├── graphrag_agent/ # 🎯 核心包 - GraphRAG智能体系统 │ ├── agents/ # 🤖 Agent模块 - 智能体实现 │ │ ├── base.py # Agent基类 │ │ ├── graph_agent.py # 基于图结构的Agent ...