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"

6 / 6 papers shown

Title
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 92 19 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 33 7 0 06 Mar 2024
Features Based Adaptive Augmentation for Graph Contrastive Learning Adnan Ali Jinlong Li OOD 16 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 17 537 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 13 213 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 242 114 0 20 Oct 2020