Semi Supervised Node Classification

Semi-supervised node classification aims to predict the labels of nodes in a graph using a limited number of labeled nodes and a wealth of unlabeled ones. Current research focuses on improving Graph Neural Networks (GNNs), including variations like Graph Transformers and hypergraph neural networks, by addressing challenges such as over-smoothing, heterophily (nodes with dissimilar labels being connected), and the impact of graph noise. These advancements aim to enhance accuracy, efficiency, and robustness, particularly in handling large graphs and diverse data distributions. The field's impact spans various applications, including social network analysis, recommendation systems, and knowledge graph reasoning.

Papers

October 7, 2023

Label-free Node Classification on Graphs with Large Language Models (LLMS)
Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
Graph Neural Network Medical LLM Graph Drawing Node Classification Semi Supervised Node Classification Dfa GNN

July 24, 2023

Addressing the Impact of Localized Training Data in Graph Neural Networks
Akansha A
Graph Neural Network Global Impact Semi Supervised Graph Structured Data Semi Supervised Node Classification Local Datasets Graph Inference

June 7, 2023

DualHGNN: A Dual Hypergraph Neural Network for Semi-Supervised Node Classification based on Multi-View Learning and Density Awareness
Jianpeng Liao, Jun Yan, Qian Tao
Semi Supervised Multi View Learning Hypergraph Neural Network Semi Supervised Node Classification Hypergraph Learning Hypergraph Attention Local Density

June 6, 2023

Optimal Inference in Contextual Stochastic Block Models
O. Duranthon, L. Zdeborová
Semi Supervised Community Detection Semi Supervised Node Classification Optimal Inference Contextual Stochastic Block Model

May 31, 2023

Graph Entropy Minimization for Semi-supervised Node Classification
Yi Luo, Guangchun Luo, Ke Qin, Aiguo Chen
Graph Neural Network Node Classification Semi Supervised Node Classification Non Parametric Entropy Optimization One Shot Aggregation

May 25, 2023

Towards Label Position Bias in Graph Neural Networks
Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang
Graph Neural Network Semi Supervised Node Classification Label Bias IC Label Word Similarity

April 3, 2023

How Graph Structure and Label Dependencies Contribute to Node Classification in a Large Network of Documents
Pirmin Lemberger, Antoine Saillenfest
Node Classification Graph Structure Graph Neural Document Relevance Semi Supervised Node Classification Large Network Label Prediction Label Dependency

March 14, 2023

GANN: Graph Alignment Neural Network for Semi-Supervised Learning
Linxuan Song, Wenxuan Tu, Sihang Zhou, Xinwang Liu, En Zhu
Semi Supervised Learning Semi Supervised Feature Alignment Semi Supervised Node Classification Graph Alignment Optimal Alignment

February 20, 2023

Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification
Yoonhyuk Choi, Jiho Choi, Taewook Ko, Chong-Kwon Kim
Graph Neural Network Subgraph Structure Semi Supervised Node Classification Subgraph Matching Edge Function

February 17, 2023

Building Shortcuts between Distant Nodes with Biaffine Mapping for Graph Convolutional Networks
Acong Zhang, Jincheng Huang, Ping Li, Kai Zhang
Convolutional Neural Network Semi Supervised Node Classification Shallow Network Deep Architecture Shortcut Feature Node Representation Learning Influential Node Affine Map

January 31, 2023

Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification
Sonny Achten, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens
Graph Neural Network Semi Supervised Node Classification Unsupervised Machine Learning Neural Implicit Kernel Classification Neighborhood Propagation

January 11, 2023

Determinate Node Selection for Semi-supervised Classification Oriented Graph Convolutional Networks
Yao Xiao, Ji Xu, Jing Yang, Shaobo Li
Semi Supervised Node Classification Semi Supervised Node Classification Supervised Graph Neural Network Node Selection

December 4, 2022

Semantic Graph Neural Network with Multi-measure Learning for Semi-supervised Classification
Junchao Lin, Yuan Wan, Jingwen Xu, Xingchen Qi
Graph Neural Network Node Representation Graph Data Semi Supervised Node Classification Semantic Graph Semi Supervised Classification Structured Graph Multi Classification

November 28, 2022

Perturb Initial Features: Generalization of Neural Networks Under Sparse Features for Semi-supervised Node Classification
Yoonhyuk Choi, Jiho Choi, Taewook Ko, Chong-Kwon Kim
Neural Network Strong Generalization Semi Supervised Node Classification Semi Supervised Node Classification Graph Filter Sparse Feature

November 1, 2022

Revisiting Heterophily in Graph Convolution Networks by Learning Representations Across Topological and Feature Spaces
Ashish Tiwari, Sresth Tosniwal, Shanmuganathan Raman
Graph Representation Heterogeneous Graph Node Representation Feature Space Semi Supervised Node Classification Graph Convolution Network Topological Representation

October 27, 2022

Beyond Homophily with Graph Echo State Networks
Domenico Tortorella, Alessio Micheli
Node Classification Graph Classification Semi Supervised Node Classification Homophilous Graph Graph Echo State Network

October 15, 2022

Improving Your Graph Neural Networks: A High-Frequency Booster
Jiaqi Sun, Lin Zhang, Shenglin Zhao, Yujiu Yang
Graph Neural Network Graph Structured Data Semi Supervised Node Classification GNN Framework Low Pas Laplacian Regularization

October 12, 2022

JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks
Jian Kang, Qinghai Zhou, Hanghang Tong
Uncertainty Quantification Graph Convolutional Network High Uncertainty Value Semi Supervised Node Classification Trustworthy Graph

October 8, 2022

Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining
Jaemin Yoo, Meng-Chieh Lee, Shubhranshu Shekhar, Christos Faloutsos
Graph Neural Network Real World Graph Semi Supervised Node Classification Graph Mining Task Graph Neural Network Attribution

August 26, 2022

Toward Robust Graph Semi-Supervised Learning against Extreme Data Scarcity
Kaize Ding, Elnaz Nouri, Guoqing Zheng, Huan Liu, Ryen White
Semi Supervised Learning Semi Supervised Data Scarcity Semi Supervised Node Classification Graph Data Augmentation Limited Labeled Data Graph Self Training