Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration

29 September 2021

Papers citing "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration"

4 / 4 papers shown

Title
Multimodal Graph Representation Learning for Robust Surgical Workflow Recognition with Adversarial Feature Disentanglement Long Bai Boyi Ma Ruohan Wang Guankun Wang Beilei Cui ... Mobarakol Islam Zhe Min Jiewen Lai Nassir Navab Hongliang Ren 2 0 0 03 May 2025
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning Mamshad Nayeem Rizve Kevin Duarte Y. S. Rawat M. Shah 171 446 0 15 Jan 2021
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 74 445 0 04 Jan 2021
Uncertainty Aware Semi-Supervised Learning on Graph Data Xujiang Zhao Feng Chen Shu Hu Jin-Hee Cho UQCV EDL BDL 87 100 0 24 Oct 2020