From Cluster Assumption to Graph Convolution: Graph-based
Semi-Supervised Learning Revisited

From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited

24 September 2023

Zheng Wang

Papers citing "From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited"

7 / 7 papers shown

Title
rLLM: Relational Table Learning with LLMs Weichen Li Xiaotong Huang Jianwu Zheng Zheng Wang Chaokun Wang Li Pan Jianhua Li LMTD 34 2 0 29 Jul 2024
Optimization-Induced Graph Implicit Nonlinear Diffusion Qi Chen Yifei Wang Yisen Wang Jiansheng Yang Zhouchen Lin DiffM 48 32 0 29 Jun 2022
Graph-based Semi-supervised Learning: A Comprehensive Review Zixing Song Xiangli Yang Zenglin Xu Irwin King 84 191 0 26 Feb 2021
L $^2$ -GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks Yuning You Tianlong Chen Zhangyang Wang Yang Shen GNN 101 82 0 30 Mar 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 270 1,944 0 09 Jun 2018
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 288 36,371 0 25 Aug 2016
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 266 31,267 0 16 Jan 2013