GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning
Benchmarks

GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks

30 May 2023

Bryan Hooi

Papers citing "GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks"

4 / 4 papers shown

Title
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges Wei Ju Siyu Yi Yifan Wang Zhiping Xiao Zhengyan Mao ... Senzhang Wang Xinwang Liu Xiao Luo Philip S. Yu Ming Zhang AI4CE 41 36 0 07 Mar 2024
Detecting Corrupted Labels Without Training a Model to Predict Zhaowei Zhu Zihao Dong Yang Liu NoLa 149 62 0 12 Oct 2021
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration Xiao Wang Hongrui Liu Chuan Shi Cheng Yang UQCV 109 115 0 29 Sep 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016