Copertina

Drop the mask! GAMM-A Taxonomy for Graph Attributes Missing Mechanisms

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Serrano, Richard, Jeudy, Baptiste, Laclau, Charlotte, Largeron, Christine
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Social and Information Networks
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Survey on Fairness for Machine Learning on Graphs
di: Laclau, Charlotte, et al.
Pubblicazione: (2022)

How Predicted Links Influence Network Evolution: Disentangling Choice and Algorithmic Feedback in Dynamic Graphs
di: Perez, Mathilde, et al.
Pubblicazione: (2026)

Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes
di: Zhao, Yige, et al.
Pubblicazione: (2023)

What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
di: Zheng, Yilun, et al.
Pubblicazione: (2024)

Attributed Graph Clustering in Collaborative Settings
di: Zhang, Rui, et al.
Pubblicazione: (2024)

Spectral Subspace Clustering for Attributed Graphs
di: Lin, Xiaoyang, et al.
Pubblicazione: (2024)

GravityGraphSAGE: Link Prediction in Directed Attributed Graphs
di: Porcedda, Riccardo, et al.
Pubblicazione: (2026)

Changepoint Detection in Highly-Attributed Dynamic Graphs
di: Penaloza, Emiliano, et al.
Pubblicazione: (2024)

Effective Clustering on Large Attributed Bipartite Graphs
di: Yang, Renchi, et al.
Pubblicazione: (2024)

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection
di: Xiao, Chunjing, et al.
Pubblicazione: (2025)

Incorporating Attributes and Multi-Scale Structures for Heterogeneous Graph Contrastive Learning
di: Jiang, Ruobing, et al.
Pubblicazione: (2025)

Effective Edge-wise Representation Learning in Edge-Attributed Bipartite Graphs
di: Wang, Hewen, et al.
Pubblicazione: (2024)

H$^2$GFM: Towards unifying Homogeneity and Heterogeneity on Text-Attributed Graphs
di: Nguyen, Trung-Kien, et al.
Pubblicazione: (2025)

Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directions
di: Li, Cheng-Te, et al.
Pubblicazione: (2024)

Learning Optimal Graph Filters for Clustering of Attributed Graphs
di: Ortiz-Bouza, Meiby, et al.
Pubblicazione: (2022)

Attacks on Node Attributes in Graph Neural Networks
di: Xu, Ying, et al.
Pubblicazione: (2024)

Mitigating Structural Overfitting: A Distribution-Aware Rectification Framework for Missing Feature Imputation
di: Song, Yifan, et al.
Pubblicazione: (2025)

Adaptive Local Clustering over Attributed Graphs
di: Zheng, Haoran, et al.
Pubblicazione: (2025)

Hierarchical Knowledge Distillation on Text Graph for Data-limited Attribute Inference
di: Li, Quan, et al.
Pubblicazione: (2024)

Pre-Training and Prompting for Few-Shot Node Classification on Text-Attributed Graphs
di: Zhao, Huanjing, et al.
Pubblicazione: (2024)

Predicting Hidden Links and Missing Nodes in Scale-Free Networks with Artificial Neural Networks
di: Pran, Rakib Hassan
Pubblicazione: (2021)

A Versatile Framework for Attributed Network Clustering via K-Nearest Neighbor Augmentation
di: Li, Yiran, et al.
Pubblicazione: (2024)

Reviving Life on the Edge: Joint Score-Based Graph Generation of Rich Edge Attributes
di: Berman, Nimrod, et al.
Pubblicazione: (2024)

Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation
di: Xiang, Sheng, et al.
Pubblicazione: (2024)

SaVe-TAG: LLM-based Interpolation for Long-Tailed Text-Attributed Graphs
di: Wang, Leyao, et al.
Pubblicazione: (2024)

Exact Matching in Correlated Networks with Node Attributes for Improved Community Recovery
di: Yang, Joonhyuk, et al.
Pubblicazione: (2025)

Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs
di: Li, Zehui, et al.
Pubblicazione: (2023)

Inference and Visualization of Community Structure in Attributed Hypergraphs Using Mixed-Membership Stochastic Block Models
di: Nakajima, Kazuki, et al.
Pubblicazione: (2024)

A Unified Graph Selective Prompt Learning for Graph Neural Networks
di: Jiang, Bo, et al.
Pubblicazione: (2024)

Predicting Healthcare System Visitation Flow by Integrating Hospital Attributes and Population Socioeconomics with Human Mobility Data
di: Lin, Binbin, et al.
Pubblicazione: (2026)

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

Brexit Means Brexit: Selection Bias, Echo Chambers, and Entrenched Opinion on Reddit
di: Rizoiu, Marian-Andrei, et al.
Pubblicazione: (2026)

Graph Structure Prompt Learning: A Novel Methodology to Improve Performance of Graph Neural Networks
di: Huang, Zhenhua, et al.
Pubblicazione: (2024)

Incorporating Heterophily into Graph Neural Networks for Graph Classification
di: Yang, Jiayi, et al.
Pubblicazione: (2022)

Unifying Generation and Prediction on Graphs with Latent Graph Diffusion
di: Zhou, Cai, et al.
Pubblicazione: (2024)

A Comprehensive Review of Community Detection in Graphs
di: Li, Jiakang, et al.
Pubblicazione: (2023)

A Scalable and Effective Alternative to Graph Transformers
di: Sancak, Kaan, et al.
Pubblicazione: (2024)

Data-centric Graph Learning: A Survey
di: Guo, Yuxin, et al.
Pubblicazione: (2023)

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

The Expressive Power of Graph Neural Networks: A Survey
di: Zhang, Bingxu, et al.
Pubblicazione: (2023)