Causality and Independence Enhancement for Biased Node Classification

v1v2 (latest)

Causality and Independence Enhancement for Biased Node Classification

14 October 2023

ArXiv (abs)PDF HTML

Papers citing "Causality and Independence Enhancement for Biased Node Classification"

7 / 7 papers shown

Title
Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts Haiyang Jiang Tong Chen Wentao Zhang Nguyen Quoc Viet Hung Yuan Yuan Yong Li Lizhen Cui OOD AI4TS 454 1 0 07 Dec 2024
CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Temporal Knowledge Graph Reasoning Jinze Sun Yongpan Sheng Lirong He Yongbin Qin Ming Liu Tao Jia CML 89 0 0 15 Aug 2024
IENE: Identifying and Extrapolating the Node Environment for Out-of-Distribution Generalization on Graphs Haoran Yang Xiaobing Pei Kai Yuan 113 0 0 02 Jun 2024
Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning Zixu Wang Bingbing Xu Yige Yuan Huawei Shen Xueqi Cheng OODD 103 2 0 25 May 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 158 3 0 19 Dec 2023
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? Yongqiang Chen Yatao Bian Kaiwen Zhou Binghui Xie Bo Han James Cheng OOD 101 41 0 29 Oct 2023
MPrompt: Exploring Multi-level Prompt Tuning for Machine Reading Comprehension Guoxin Chen Yiming Qian Bowen Wang Liangzhi Li 53 7 0 27 Oct 2023

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.