Cover Image

Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Subramonian, Arjun, Kang, Jian, Sun, Yizhou
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Social and Information Networks
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction
by: Subramonian, Arjun, et al.
Published: (2023)

Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of the WL Test
by: Subramonian, Arjun, et al.
Published: (2023)

Topologically-Stabilized Graph Neural Networks: Empirical Robustness Across Domains
by: Losic, Jelena
Published: (2025)

BeMap: Balanced Message Passing for Fair Graph Neural Network
by: Lin, Xiao, et al.
Published: (2023)

Non-Euclidean Mixture Model for Social Network Embedding
by: Iyer, Roshni G., et al.
Published: (2024)

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

Forward Learning of Graph Neural Networks
by: Park, Namyong, et al.
Published: (2024)

FairACE: Achieving Degree Fairness in Graph Neural Networks via Contrastive and Adversarial Group-Balanced Training
by: Liu, Jiaxin, et al.
Published: (2025)

Mitigating Bias in Graph Hyperdimensional Computing
by: Liu, Yezi, et al.
Published: (2025)

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

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

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

Graph Neural Networks with Diverse Spectral Filtering
by: Guo, Jingwei, et al.
Published: (2023)

Feature Selection and Extraction for Graph Neural Networks
by: Acharya, Deepak Bhaskar, et al.
Published: (2019)

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

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

NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
by: Wang, Zhonghao, et al.
Published: (2024)

GraphMU: Repairing Robustness of Graph Neural Networks via Machine Unlearning
by: Wu, Tao, et al.
Published: (2024)

Manufacturing Service Capability Prediction with Graph Neural Networks
by: Li, Yunqing, et al.
Published: (2024)

Revisiting the Message Passing in Heterophilous Graph Neural Networks
by: Zheng, Zhuonan, et al.
Published: (2024)

Conditional Local Feature Encoding for Graph Neural Networks
by: Wang, Yongze, et al.
Published: (2024)

Demystifying Oversmoothing in Attention-Based Graph Neural Networks
by: Wu, Xinyi, et al.
Published: (2023)

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

Do We Trust What They Say or What They Do? A Multimodal User Embedding Provides Personalized Explanations
by: Ren, Zhicheng, et al.
Published: (2024)

Dynamic Graph with Similarity-Aware Attention Graph Neural Network for Recommender Systems
by: Senapati, Aadarsh, et al.
Published: (2026)

Link Prediction with Physics-Inspired Graph Neural Networks
by: Di Francesco, Andrea Giuseppe, et al.
Published: (2024)

Bipartite Graph Variational Auto-Encoder with Fair Latent Representation to Account for Sampling Bias in Ecological Networks
by: Anakok, Emre, et al.
Published: (2024)

The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges
by: Luan, Sitao, et al.
Published: (2024)

Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs
by: Heeg, Franziska, et al.
Published: (2023)

Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure
by: Sato, Ryoma
Published: (2023)

Interactive Event Sifting using Bayesian Graph Neural Networks
by: Nascimento, José, et al.
Published: (2024)

GRAPHGINI: Fostering Individual and Group Fairness in Graph Neural Networks
by: Sirohi, Anuj Kumar, et al.
Published: (2024)

A Graph Neural Network deep-dive into successful counterattacks
by: Bekkers, Joris, et al.
Published: (2024)

PropEnc: A Property Encoder for Graph Neural Networks
by: Said, Anwar, et al.
Published: (2024)

Understanding the Robustness of Graph Neural Networks against Adversarial Attacks
by: Wu, Tao, et al.
Published: (2024)

Transferability of Graph Neural Networks using Graphon and Sampling Theories
by: Neuman, A. Martina, et al.
Published: (2023)

GNNAnatomy: Rethinking Model-Level Explanations for Graph Neural Networks
by: Lu, Hsiao-Ying, et al.
Published: (2024)

A Survey of Graph Neural Networks for Social Recommender Systems
by: Sharma, Kartik, et al.
Published: (2022)

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

InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections
by: Qin, Meng, et al.
Published: (2025)