:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Cui, Nan, Wang, Xiuling, Wang, Wendy Hui, Chen, Violet, Ning, Yue
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2310.12350
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Lightweight Fairness for LLM-Based Recommendations via Kernelized Projection and Gated Adapters
by: Cui, Nan, et al.
Published: (2026)

Benchmarking Fairness-aware Graph Neural Networks in Knowledge Graphs
by: Sasaki, Yuya
Published: (2025)

Safeguarding Graph Neural Networks against Topology Inference Attacks
by: Fu, Jie, et al.
Published: (2025)

Communication-efficient Federated Graph Classification via Generative Diffusion Modeling
by: Wang, Xiuling, et al.
Published: (2026)

FnRGNN: Distribution-aware Fairness in Graph Neural Network
by: Park, Soyoung, et al.
Published: (2025)

Quantum Graph Attention Network: A Novel Quantum Multi-Head Attention Mechanism for Graph Learning
by: Ning, An, et al.
Published: (2025)

Adaptive Dual Prompting: Hierarchical Debiasing for Fairness-aware Graph Neural Networks
by: Yang, Yuhan, et al.
Published: (2025)

Homophily-aware Supervised Contrastive Counterfactual Augmented Fair Graph Neural Network
by: Kejani, Mahdi Tavassoli, et al.
Published: (2026)

FairGU: Fairness-aware Graph Unlearning in Social Networks
by: Luo, Renqiang, et al.
Published: (2026)

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

Adversarial Attacks on Fairness of Graph Neural Networks
by: Zhang, Binchi, et al.
Published: (2023)

Quantum Pointwise Convolution: A Flexible and Scalable Approach for Neural Network Enhancement
by: Ning, An, et al.
Published: (2024)

Bridging the Fairness Divide: Achieving Group and Individual Fairness in Graph Neural Networks
by: Zhan, Duna, et al.
Published: (2024)

FairGC: Fairness-aware Graph Condensation
by: Gao, Yihan, et al.
Published: (2026)

Improving Fairness in Graph Neural Networks via Counterfactual Debiasing
by: Wo, Zengyi, et al.
Published: (2025)

A Topology-aware Graph Coarsening Framework for Continual Graph Learning
by: Han, Xiaoxue, et al.
Published: (2024)

Explaining Graph Neural Networks via Structure-aware Interaction Index
by: Bui, Ngoc, et al.
Published: (2024)

FairFLRep: Fairness aware fault localization and repair of Deep Neural Networks
by: Openja, Moses, et al.
Published: (2025)

Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning
by: Sun, Li, et al.
Published: (2024)

FairGSE: Fairness-Aware Graph Neural Network without High False Positive Rates
by: Ye, Zhenqiang, et al.
Published: (2025)

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

PFAttack: Stealthy Attack Bypassing Group Fairness in Federated Learning
by: Gao, Jiashi, et al.
Published: (2024)

Heterogeneous Graph Neural Networks with Loss-decrease-aware Curriculum Learning
by: Wang, Yili
Published: (2024)

DFed-SST: Building Semantic- and Structure-aware Topologies for Decentralized Federated Graph Learning
by: Guo, Lianshuai, et al.
Published: (2025)

FairGT: A Fairness-aware Graph Transformer
by: Luo, Renqiang, et al.
Published: (2024)

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
by: Dai, Enyan, et al.
Published: (2022)

Fed-Listing: Federated Label Distribution Inference in Graph Neural Networks
by: Nakarmi, Suprim, et al.
Published: (2026)

Cluster-Enhanced Federated Graph Neural Network for Recommendation
by: Wang, Haiyan, et al.
Published: (2024)

Feature-Aware One-Shot Federated Learning via Hierarchical Token Sequences
by: Liu, Shudong, et al.
Published: (2026)

Towards Group Fairness with Multiple Sensitive Attributes in Federated Foundation Models
by: Yang, Yuning, et al.
Published: (2025)

Rethinking Structure Learning For Graph Neural Networks
by: Zheng, Yilun, et al.
Published: (2024)

ComFairGNN: Community Fair Graph Neural Network
by: Sium, Yonas, et al.
Published: (2024)

Dual-Frequency Filtering Self-aware Graph Neural Networks for Homophilic and Heterophilic Graphs
by: Yang, Yachao, et al.
Published: (2024)

SGAC: A Graph Neural Network Framework for Imbalanced and Structure-Aware AMP Classification
by: Wang, Yingxu, et al.
Published: (2024)

Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
by: Fan, Shaohua, et al.
Published: (2021)

Inference Attacks Against Graph Generative Diffusion Models
by: Wang, Xiuling, et al.
Published: (2026)

Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections
by: Luo, Zihan, et al.
Published: (2024)

Efficient Topology-aware Data Augmentation for High-Degree Graph Neural Networks
by: Lai, Yurui, et al.
Published: (2024)

FedCD: A Fairness-aware Federated Cognitive Diagnosis Framework
by: Yang, Shangshang, et al.
Published: (2025)

FairQuant: Certifying and Quantifying Fairness of Deep Neural Networks
by: Kim, Brian Hyeongseok, et al.
Published: (2024)