Copertina

Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Huang, Jincheng, Mo, Yujie, Shi, Xiaoshuang, Feng, Lei, Zhu, Xiaofeng
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

The Final Layer Holds the Key: A Unified and Efficient GNN Calibration Framework
di: Huang, Jincheng, et al.
Pubblicazione: (2025)

HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
di: Mo, Yujie, et al.
Pubblicazione: (2024)

Correlation-Aware Graph Convolutional Networks for Multi-Label Node Classification
di: Bei, Yuanchen, et al.
Pubblicazione: (2024)

Node Classification via Semantic-Structural Attention-Enhanced Graph Convolutional Networks
di: Zhu, Hongyin
Pubblicazione: (2024)

Graph Convolutional Network For Semi-supervised Node Classification With Subgraph Sketching
di: Huang, Zibin, et al.
Pubblicazione: (2024)

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification
di: Zaz, Brown, et al.
Pubblicazione: (2026)

SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks
di: Lu, Weigang, et al.
Pubblicazione: (2021)

InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning
di: Huang, Zhe, et al.
Pubblicazione: (2024)

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels
di: Dong, Xiangyu, et al.
Pubblicazione: (2025)

PAC-Bayesian Generalization Bounds for Graph Convolutional Networks on Inductive Node Classification
di: Tang, Huayi, et al.
Pubblicazione: (2025)

Formal Verification of Graph Convolutional Networks with Uncertain Node Features and Uncertain Graph Structure
di: Ladner, Tobias, et al.
Pubblicazione: (2024)

Exact Fit Attention in Node-Holistic Graph Convolutional Network for Improved EEG-Based Driver Fatigue Detection
di: Xu, Meiyan, et al.
Pubblicazione: (2025)

Virtual Node Generation for Node Classification in Sparsely-Labeled Graphs
di: Cui, Hang, et al.
Pubblicazione: (2024)

Structure-Aware Consensus Network on Graphs with Few Labeled Nodes
di: Xu, Shuaike, et al.
Pubblicazione: (2024)

Incremental Label Distribution Learning with Scalable Graph Convolutional Networks
di: Jia, Ziqi, et al.
Pubblicazione: (2024)

Sepsis Prediction Using Graph Convolutional Networks over Patient-Feature-Value Triplets
di: Dan, Bozhi, et al.
Pubblicazione: (2025)

Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias
di: Shi, Zhihao, et al.
Pubblicazione: (2023)

Self-Attention Empowered Graph Convolutional Network for Structure Learning and Node Embedding
di: Jiang, Mengying, et al.
Pubblicazione: (2024)

FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients
di: Qiu, Xinchi, et al.
Pubblicazione: (2024)

Transfer Learning Under High-Dimensional Graph Convolutional Regression Model for Node Classification
di: Chen, Jiachen, et al.
Pubblicazione: (2024)

Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation
di: Chen, Boqi, et al.
Pubblicazione: (2024)

L^2GC:Lorentzian Linear Graph Convolutional Networks for Node Classification
di: Liang, Qiuyu, et al.
Pubblicazione: (2024)

Joint Graph Convolution and Sequential Modeling for Scalable Network Traffic Estimation
di: Jiang, Nan, et al.
Pubblicazione: (2025)

Graph-Based Uncertainty-Aware Self-Training with Stochastic Node Labeling
di: Liu, Tom, et al.
Pubblicazione: (2025)

Coefficient Decomposition for Spectral Graph Convolution
di: Huang, Feng, et al.
Pubblicazione: (2024)

The Transferability of Downsamped Sparse Graph Convolutional Networks
di: Shu, Qinji, et al.
Pubblicazione: (2024)

Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning
di: Luo, Yuankai, et al.
Pubblicazione: (2024)

Graph Unlearning: Efficient Node Removal in Graph Neural Networks
di: Guan, Faqian, et al.
Pubblicazione: (2025)

Adapt, Agree, Aggregate: Semi-Supervised Ensemble Labeling for Graph Convolutional Networks
di: Abdolali, Maryam, et al.
Pubblicazione: (2025)

Review of blockchain application with Graph Neural Networks, Graph Convolutional Networks and Convolutional Neural Networks
di: Ancelotti, Amy, et al.
Pubblicazione: (2024)

Lying Graph Convolution: Learning to Lie for Node Classification Tasks
di: Castellana, Daniele
Pubblicazione: (2024)

On Leveraging Unlabeled Data for Concurrent Positive-Unlabeled Classification and Robust Generation
di: Yu, Bing, et al.
Pubblicazione: (2020)

Divide-and-Conquer for Enhancing Unlabeled Learning, Stability, and Plasticity in Semi-supervised Continual Learning
di: Duan, Yue, et al.
Pubblicazione: (2025)

Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data
di: Zhang, Jiahan, et al.
Pubblicazione: (2024)

Mixed Graph Contrastive Network for Semi-Supervised Node Classification
di: Yang, Xihong, et al.
Pubblicazione: (2022)

GraphSB: Boosting Imbalanced Node Classification on Graphs through Structural Balance
di: Wang, Zhixiao, et al.
Pubblicazione: (2026)

Higher-order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes
di: Huang, Yiming, et al.
Pubblicazione: (2023)

Visualization Tasks for Unlabeled Graphs
di: Oddo, Matt I. B., et al.
Pubblicazione: (2025)

Transformer with Koopman-Enhanced Graph Convolutional Network for Spatiotemporal Dynamics Forecasting
di: Wang, Zekai, et al.
Pubblicazione: (2025)

MLGIB: Multi-Label Graph Information Bottleneck for Expressive and Robust Message Passing
di: Wu, Chaokai, et al.
Pubblicazione: (2026)