Imagen de Portada

Research and Implementation of Data Enhancement Techniques for Graph Neural Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Gu, Jingzhao, Huang, Haoyang
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Capacity-Aware Mixture Law Enables Efficient LLM Data Optimization
por: Li, Jingwei, et al.
Publicado: (2026)

Data Mixing Can Induce Phase Transitions in Knowledge Acquisition
por: Gu, Xinran, et al.
Publicado: (2025)

A Quadratic Synchronization Rule for Distributed Deep Learning
por: Gu, Xinran, et al.
Publicado: (2023)

Out-of-Distribution Generalized Dynamic Graph Neural Network with Disentangled Intervention and Invariance Promotion
por: Zhang, Zeyang, et al.
Publicado: (2023)

Iterative Graph Neural Network Enhancement via Frequent Subgraph Mining of Explanations
por: Naik, Harish G., et al.
Publicado: (2024)

Fredholm Integral Equations Neural Operator (FIE-NO) for Data-Driven Boundary Value Problems
por: Jiang, Haoyang, et al.
Publicado: (2024)

Fast and Multiphase Rates for Nearest Neighbor Classifiers
por: Yang, Pengkun, et al.
Publicado: (2023)

RSEA-MVGNN: Multi-View Graph Neural Network with Reliable Structural Enhancement and Aggregation
por: Chen, Junyu, et al.
Publicado: (2024)

Analysis of Anonymous User Interaction Relationships and Prediction of Advertising Feedback Based on Graph Neural Network
por: Dai, Yanjun, et al.
Publicado: (2025)

Learning Pore-scale Multi-phase Flow from Experimental Data with Graph Neural Network
por: Gu, Yuxuan, et al.
Publicado: (2024)

Towards Fair Graph Neural Networks via Graph Counterfactual without Sensitive Attributes
por: Wang, Xuemin, et al.
Publicado: (2024)

Factorized Explainer for Graph Neural Networks
por: Huang, Rundong, et al.
Publicado: (2023)

GraphTorque: Torque-Driven Rewiring Graph Neural Network
por: Huang, Sujia, et al.
Publicado: (2025)

Scalable Model Merging with Progressive Layer-wise Distillation
por: Xu, Jing, et al.
Publicado: (2025)

Optimizing Long-tailed Link Prediction in Graph Neural Networks through Structure Representation Enhancement
por: Wang, Yakun, et al.
Publicado: (2024)

Towards Migrating Neural Network Implementations
por: Daoudi, Nadia, et al.
Publicado: (2025)

Interpretable Graph Neural Networks for Heterogeneous Tabular Data
por: Alkhatib, Amr, et al.
Publicado: (2024)

OpenGLT: A Comprehensive Benchmark of Graph Neural Networks for Graph-Level Tasks
por: Li, Haoyang, et al.
Publicado: (2025)

Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
por: Xu, Jing, et al.
Publicado: (2024)

On the Condition Number Dependency in Bilevel Optimization
por: Chen, Lesi, et al.
Publicado: (2025)

Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks
por: Gu, Jing, et al.
Publicado: (2024)

Heterophilous Distribution Propagation for Graph Neural Networks
por: Zheng, Zhuonan, et al.
Publicado: (2024)

Graph Coordinates and Conventional Neural Networks -- An Alternative for Graph Neural Networks
por: Qin, Zheyi, et al.
Publicado: (2023)

Interpretable Graph Neural Networks for Tabular Data
por: Alkhatib, Amr, et al.
Publicado: (2023)

A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications
por: Han, Jiaqi, et al.
Publicado: (2024)

Data Mining in Transportation Networks with Graph Neural Networks: A Review and Outlook
por: Xue, Jiawei, et al.
Publicado: (2025)

Spiking Graph Neural Network on Riemannian Manifolds
por: Sun, Li, et al.
Publicado: (2024)

Implicit vs Unfolded Graph Neural Networks
por: Yang, Yongyi, et al.
Publicado: (2021)

Cooperative Graph Neural Networks
por: Finkelshtein, Ben, et al.
Publicado: (2023)

NeuBM: Mitigating Model Bias in Graph Neural Networks through Neutral Input Calibration
por: Gu, Jiawei, et al.
Publicado: (2025)

Data Difficulty and the Generalization--Extrapolation Tradeoff in LLM Fine-Tuning
por: Liu, Siyuan, et al.
Publicado: (2026)

Preference and Concurrence Aware Bayesian Graph Neural Networks for Recommender Systems
por: Gu, Hongjian, et al.
Publicado: (2023)

Demystifying Distributed Training of Graph Neural Networks for Link Prediction
por: Huang, Xin, et al.
Publicado: (2025)

NaNa and MiGu: Semantic Data Augmentation Techniques to Enhance Protein Classification in Graph Neural Networks
por: Lan, Yi-Shan, et al.
Publicado: (2024)

Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks
por: Sainsbury-Dale, Matthew, et al.
Publicado: (2023)

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

Post-Hoc Robustness Enhancement in Graph Neural Networks with Conditional Random Fields
por: Abbahaddou, Yassine, et al.
Publicado: (2024)

Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural Networks
por: Ma, Rongrong, et al.
Publicado: (2024)

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data
por: Qi, Yijiashun, et al.
Publicado: (2025)

Speech Enhancement Using Continuous Embeddings of Neural Audio Codec
por: Li, Haoyang, et al.
Publicado: (2025)