From Overfitting to Robustness: Quantity, Quality, and Variety Oriented
Negative Sample Selection in Graph Contrastive Learning

From Overfitting to Robustness: Quantity, Quality, and Variety Oriented Negative Sample Selection in Graph Contrastive Learning

21 June 2024

Huanhuan Chen

Ali Kashif Bashir

Papers citing "From Overfitting to Robustness: Quantity, Quality, and Variety Oriented Negative Sample Selection in Graph Contrastive Learning"

6 / 6 papers shown

Title
A Binary Classification Social Network Dataset for Graph Machine Learning Adnan Ali Jinglong Li Huanhuan Chen AlMotasem Bellah Al Ajlouni GNN 57 0 0 04 Mar 2025
Neighborhood-based Hard Negative Mining for Sequential Recommendation Lu Fan Jiashu Pu Rongsheng Zhang Xiao-Ming Wu 20 9 0 12 Jun 2023
Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapath Shuai Ma Jian-wei Liu Xin Zuo SSL 32 5 0 09 Sep 2022
Learning Graph Augmentations to Learn Graph Representations Kaveh Hassani Amir Hosein Khas Ahmadi 34 21 0 24 Jan 2022
Augmentation-Free Self-Supervised Learning on Graphs Namkyeong Lee Junseok Lee Chanyoung Park 54 203 0 05 Dec 2021
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 29,632 0 16 Jan 2013