Self-supervised Graph Neural Networks without explicit negative sampling

Self-supervised Graph Neural Networks without explicit negative sampling

27 March 2021

Zekarias T. Kefato

Sarunas Girdzijauskas

Papers citing "Self-supervised Graph Neural Networks without explicit negative sampling"

9 / 9 papers shown

Title
Tensor-Fused Multi-View Graph Contrastive Learning Yujia Wu Junyi Mo Elynn Chen Yuzhou Chen 29 1 0 20 Oct 2024
A Comprehensive Survey on Data Augmentation Zaitian Wang Pengfei Wang Kunpeng Liu Pengyang Wang Yanjie Fu Chang-Tien Lu Charu Aggarwal Jian Pei Yuanchun Zhou ViT 109 22 0 15 May 2024
A Teacher-Free Graph Knowledge Distillation Framework with Dual Self-Distillation Lirong Wu Haitao Lin Zhangyang Gao Guojiang Zhao Stan Z. Li 40 8 0 06 Mar 2024
Data Augmentation on Graphs: A Technical Survey Jiajun Zhou Chenxuan Xie Shengbo Gong Z. Wen Xiangyu Zhao Qi Xuan Xiaoniu Yang AI4TS 24 8 0 20 Dec 2022
Analyzing Data-Centric Properties for Graph Contrastive Learning Puja Trivedi Ekdeep Singh Lubana Mark Heimann Danai Koutra Jayaraman J. Thiagarajan 30 11 0 04 Aug 2022
Features Based Adaptive Augmentation for Graph Contrastive Learning Adnan Ali Jinlong Li OOD 24 7 0 05 Jul 2022
GraphMAE: Self-Supervised Masked Graph Autoencoders Zhenyu Hou Xiao Liu Yukuo Cen Yuxiao Dong Hongxia Yang C. Wang Jie Tang SSL 45 546 0 22 May 2022
Large-Scale Representation Learning on Graphs via Bootstrapping S. Thakoor Corentin Tallec M. G. Azar Mehdi Azabou Eva L. Dyer Rémi Munos Petar Velivcković Michal Valko SSL 29 217 0 12 Feb 2021
BYOL works even without batch statistics Pierre Harvey Richemond Jean-Bastien Grill Florent Altché Corentin Tallec Florian Strub ... Samuel L. Smith Soham De Razvan Pascanu Bilal Piot Michal Valko SSL 250 114 0 20 Oct 2020