BeMap: Balanced Message Passing for Fair Graph Neural Network

7 June 2023

Papers citing "BeMap: Balanced Message Passing for Fair Graph Neural Network"

6 / 6 papers shown

Title
How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark Ruizhong Qiu Weiliang Will Zeng Hanghang Tong James Ezick Christopher Lott 88 16 0 20 Feb 2025
Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs Shengyin Sun Yuxiang Ren Chen Ma Xuecang Zhang 115 20 0 24 Nov 2023
Fairness-aware Message Passing for Graph Neural Networks Huaisheng Zhu Guoji Fu Zhimeng Guo Zhiwei Zhang Teng Xiao Suhang Wang 21 6 0 19 Jun 2023
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud Weijing Shi Ragunathan R. Rajkumar 3DPC 171 738 0 02 Mar 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 338 4,230 0 23 Aug 2019
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 163 25,296 0 09 Jun 2011