Cover Image

Heterogeneous Graph Generation: A Hierarchical Approach using Node Feature Pooling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ghosh, Hritaban, Changyu, Chen, Sinha, Arunesh, Sural, Shamik
Format:	Preprint
Published:	2024
Subjects:	Social and Information Networks Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Strategic Incentivization for Locally Differentially Private Federated Learning
by: Pagoti, Yashwant Krishna, et al.
Published: (2025)

A GAN Approach for Node Embedding in Heterogeneous Graphs Using Subgraph Sampling
by: Hsu, Hung-Chun, et al.
Published: (2023)

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

LLMs Between the Nodes: Community Discovery Beyond Vectors
by: Gujral, Ekta, et al.
Published: (2025)

Encoder Embedding for General Graph and Node Classification
by: Shen, Cencheng
Published: (2024)

NodeNAS: Node-Specific Graph Neural Architecture Search for Out-of-Distribution Generalization
by: Wang, Qiyi, et al.
Published: (2025)

MDL-Pool: Adaptive Multilevel Graph Pooling Based on Minimum Description Length
by: von Pichowski, Jan, et al.
Published: (2024)

Neural Graph Generator: Feature-Conditioned Graph Generation using Latent Diffusion Models
by: Evdaimon, Iakovos, et al.
Published: (2024)

Classifying Nodes in Graphs without GNNs
by: Winter, Daniel, et al.
Published: (2024)

A Probabilistic Model for Node Classification in Directed Graphs
by: Huerta, Diego, et al.
Published: (2025)

HiGen: Hierarchical Graph Generative Networks
by: Karami, Mahdi
Published: (2023)

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

Fully-inductive Node Classification on Arbitrary Graphs
by: Zhao, Jianan, et al.
Published: (2024)

Disambiguated Node Classification with Graph Neural Networks
by: Zhao, Tianxiang, et al.
Published: (2024)

Enhancing Fake-News Detection with Node-Level Topological Features
by: Xu, Kaiyuan
Published: (2025)

Novel Node Category Detection Under Subpopulation Shift
by: Chung, Hsing-Huan, et al.
Published: (2024)

A Survey on Signed Graph Embedding: Methods and Applications
by: Ghosh, Shrabani
Published: (2024)

GraphSB: Boosting Imbalanced Node Classification on Graphs through Structural Balance
by: Zhu, Chaofan, et al.
Published: (2025)

When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability
by: Luan, Sitao, et al.
Published: (2023)

BANGS: Game-Theoretic Node Selection for Graph Self-Training
by: Wang, Fangxin, et al.
Published: (2024)

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

Subgraph Pooling: Tackling Negative Transfer on Graphs
by: Wang, Zehong, et al.
Published: (2024)

Generating Human Understandable Explanations for Node Embeddings
by: Shafi, Zohair, et al.
Published: (2024)

Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach
by: Gao, Hang, et al.
Published: (2024)

Rethinking Semi-Supervised Node Classification with Self-Supervised Graph Clustering
by: Wang, Songbo, et al.
Published: (2025)

Out-of-Distribution Detection in Heterogeneous Graphs via Energy Propagation
by: Yin, Tao, et al.
Published: (2025)

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

Is Graph Convolution Always Beneficial For Every Feature?
by: Zheng, Yilun, et al.
Published: (2024)

Toward Scalable Graph Unlearning: A Node Influence Maximization based Approach
by: Li, Xunkai, et al.
Published: (2025)

TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
by: Gastinger, Julia, et al.
Published: (2024)

Interpretable and Adaptive Node Classification on Heterophilic Graphs via Combinatorial Scoring and Hybrid Learning
by: Vahidi, Soroush
Published: (2025)

Heterogeneous Graph Neural Network on Semantic Tree
by: Guan, Mingyu, et al.
Published: (2024)

Differentiable Tripartite Modularity for Clustering Heterogeneous Graphs
by: Hurpeau, Benoît
Published: (2026)

Homophily-aware Heterogeneous Graph Contrastive Learning
by: Wang, Haosen, et al.
Published: (2025)

Epidemiology-informed Graph Neural Network for Heterogeneity-aware Epidemic Forecasting
by: Zheng, Yufan, et al.
Published: (2024)

Graph Contrastive Learning with Low-Rank Regularization and Low-Rank Attention for Noisy Node Classification
by: Wang, Yancheng, et al.
Published: (2024)

Enhancing Graph Representation Learning with Localized Topological Features
by: Yan, Zuoyu, et al.
Published: (2025)

Echoless Label-Based Pre-computation for Memory-Efficient Heterogeneous Graph Learning
by: Hu, Jun, et al.
Published: (2025)

Deep Structural Knowledge Exploitation and Synergy for Estimating Node Importance Value on Heterogeneous Information Networks
by: Chen, Yankai, et al.
Published: (2024)

Efficient Heterogeneous Graph Learning via Random Projection
by: Hu, Jun, et al.
Published: (2023)