FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs | Paper Citation Record

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This paper cites Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Personalized subgraph federated learning

Reference 2

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This paper cites Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Node classification in social networks

Reference 4

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Fast unfolding of communities in large networks

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Beyond low-frequency information in graph convolutional networks

Reference 6

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Geometric deep learning: going beyond euclidean data

Reference 7

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This paper cites FedGL: Federated Graph Learning Framework with Global Self-Supervision.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs FedGL: Federated Graph Learning Framework with Global Self-Supervision

Reference 8

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This paper cites Fede: Embedding knowledge graphs in federated setting.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Fede: Embedding knowledge graphs in federated setting

Reference 9

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This paper cites Iterative deep graph learning for graph neural networks: Better and robust node embeddings.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Iterative deep graph learning for graph neural networks: Better and robust node embeddings

Reference 10

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This paper cites Adaptive Universal Generalized PageRank Graph Neural Network.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Adaptive Universal Generalized PageRank Graph Neural Network

Reference 11

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Grapheditor: An efficient graph representation learning and unlearning approach

Reference 12

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This paper cites A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability

Reference 13

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This paper cites Benchmarking graph neural networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Benchmarking graph neural networks

Reference 14

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This paper cites Fairness through awareness.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Fairness through awareness

Reference 15

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This paper cites Variational inference for graph convolutional networks in the absence of graph data and adversarial settings.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Variational inference for graph convolutional networks in the absence of graph data and adversarial settings

Reference 16

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph neural networks for social recommendation

Reference 17

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This paper cites Learning discrete structures for graph neural networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Learning discrete structures for graph neural networks

Reference 18

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This paper cites Federated learning: A signal processing perspective.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Federated learning: A signal processing perspective

Reference 19

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This paper cites Diffusion improves graph learning.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Diffusion improves graph learning

Reference 20

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This paper cites Attribute inference attacks in online social networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Attribute inference attacks in online social networks

Reference 21

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This paper cites SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks

Reference 22

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This paper cites Ieee-cis fraud detection, 2019.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Ieee-cis fraud detection, 2019

Reference 23

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Semi-supervised learning with graph learning-convolutional networks

Reference 24

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph structure learning for robust graph neural networks

Reference 25

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Metis: A software package for partitioning unstructured graphs, partitioning meshes, and computing fill-reducing orderings of sparse matrices

Reference 26

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Differentiable graph module (dgm) for graph convolutional networks

Reference 27

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This paper cites How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

Reference 28

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Adam: A Method for Stochastic Optimization

Reference 29

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Semi-Supervised Classification with Graph Convolutional Networks

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Rethinking graph transformers with spectral attention

Reference 31

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Federated learning over coupled graphs

Reference 32

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Adaptive graph convolutional neural networks

Reference 33

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Adaptive graph convolutional neural networks

Reference 34

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Federated learning: Challenges, methods, and future directions

Reference 35

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Finding global homophily in graph neural networks when meeting heterophily

Reference 36

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Gslb: the graph structure learning benchmark

Reference 37

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Towards deeper graph neural networks

Reference 38

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Federated Graph Neural Networks: Overview, Techniques and Challenges

Reference 39

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Federated graph neural networks: Overview, techniques, and challenges

Reference 40

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Towards unsupervised deep graph structure learning

Reference 41

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Beyond smoothing: Unsupervised graph representation learning with edge heterophily discriminating

Reference 42

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Egnn: Graph structure learning based on evolutionary computation helps more in graph neural networks

Reference 43

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs STFL: A Temporal-Spatial Federated Learning Framework for Graph Neural Networks

Reference 44

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Revisiting heterophily for graph neural networks

Reference 45

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Learning to drop: Robust graph neural network via topological denoising

Reference 46

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Learning disentangled representations for recommendation

Reference 47

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This paper cites Is Homophily a Necessity for Graph Neural Networks?.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Is Homophily a Necessity for Graph Neural Networks?

Reference 48

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?

Reference 49

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Communication-efficient learning of deep networks from decentralized data

Reference 50

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Sgnn: A graph neural network based federated learning approach by hiding structure

Reference 51

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Query-driven active surveying for collective classification

Reference 52

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Cosine similarity metric learning for face verification

Reference 53

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Netprobe: a fast and scalable system for fraud detection in online auction networks

Reference 54

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Differentially private federated knowledge graphs embedding

Reference 55

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Multi-scale attributed node embedding

Reference 56

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs The graph neural network model

Reference 57

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Collective classification in network data

Reference 58

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This paper cites Graph neural networks in particle physics.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph neural networks in particle physics

Reference 59

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph structure learning with variational information bottleneck

Reference 60

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This paper cites Breaking the limit of graph neural networks by improving the assortativity of graphs with local mixing patterns.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Breaking the limit of graph neural networks by improving the assortativity of graphs with local mixing patterns

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.891929Z

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This paper cites Federated learning on non-iid graphs via structural knowledge sharing.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Federated learning on non-iid graphs via structural knowledge sharing

Reference 62

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Observation 8aeb098b-58aa-4b8d-9d5a-042b58d20c98 · outbound

This paper cites Social influence analysis in large-scale networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Social influence analysis in large-scale networks

Reference 63

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Social influence analysis in large-scale networks

Reference 64

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This paper cites Graph attention networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph attention networks

Reference 65

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This paper cites Confederated learning: Federated learning with decentralized edge servers.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Confederated learning: Federated learning with decentralized edge servers

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.813783Z

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Observation 05b8e346-225f-4016-8da9-7c2e024e462a · outbound

This paper cites Am-gcn: Adaptive multi-channel graph convolutional networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Am-gcn: Adaptive multi-channel graph convolutional networks

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.796650Z

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Observation 697c3bd1-b8f1-49f7-b637-508f16404ab7 · outbound

This paper cites Nodeformer: A scalable graph structure learning transformer for node classification.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Nodeformer: A scalable graph structure learning transformer for node classification

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.780316Z

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Session-based recommendation with graph neural networks

Reference 69

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph information bottleneck

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.750629Z

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This paper cites A comprehensive survey on graph neural networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs A comprehensive survey on graph neural networks

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.735204Z

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This paper cites Graph learning: A survey.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph learning: A survey

Reference 72

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph neural networks in node classification: survey and evaluation

Reference 73

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Federated graph classification over non-iid graphs

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.699743Z

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Federated node classification over graphs with latent link-type heterogeneity

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.682912Z

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This paper cites How Powerful are Graph Neural Networks?.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs How Powerful are Graph Neural Networks?

Reference 76

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Representation learning on graphs with jumping knowledge networks

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.665637Z

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Observation 07a3ff2a-4c9c-4894-9edd-1cd9ca58661c · outbound

This paper cites Two sides of the same coin: Heterophily and oversmoothing in graph convolutional neural networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Two sides of the same coin: Heterophily and oversmoothing in graph convolutional neural networks

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.644748Z

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This paper cites Diverse message passing for attribute with heterophily.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Diverse message passing for attribute with heterophily

Reference 79

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph pointer neural networks

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.617282Z

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This paper cites Revisiting semi-supervised learning with graph embeddings.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Revisiting semi-supervised learning with graph embeddings

Reference 81

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Fedfm: Anchor-based feature matching for data heterogeneity in federated learning

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.591582Z

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This paper cites The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.575461Z

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This paper cites Graph convolutional neural networks for web-scale recommender systems.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph convolutional neural networks for web-scale recommender systems

Reference 84

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph-revised convolutional network

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.548425Z

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This paper cites Explainability in graph neural networks: A taxonomic survey.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Explainability in graph neural networks: A taxonomic survey

Reference 86

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 87

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This paper cites Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation

Reference 88

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Subgraph federated learning with missing neighbor generation

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.519305Z

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This paper cites Bayesian graph convolutional neural networks for semi-supervised classification.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Bayesian graph convolutional neural networks for semi-supervised classification

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.501219Z

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Heterogeneous graph structure learning for graph neural networks

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.483021Z

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This paper cites Data augmentation for graph neural networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Data augmentation for graph neural networks

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.466459Z

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This paper cites GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks

Reference 93

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Asfgnn: Automated separated-federated graph neural network

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.450652Z

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Observation 96bf75a0-89d3-4d51-86c5-7dfd8ea5834c · outbound

This paper cites Graph Neural Networks for Graphs with Heterophily: A Survey.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph Neural Networks for Graphs with Heterophily: A Survey

Reference 95

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Finding the missing-half: Graph complementary learning for homophily-prone and heterophily-prone graphs

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.434084Z

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Observation ae5d752c-c929-4a8c-8de8-2259a1f9ca40 · outbound

This paper cites Graph neural networks: A review of methods and applications.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Graph neural networks: A review of methods and applications

Reference 97

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FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Beyond homophily in graph neural networks: Current limitations and effective designs

Reference 98

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Observation f243fcbe-b7c3-4c4d-83fd-1f2185e82da9 · outbound

This paper cites Mixedad: A scalable algorithm for detecting mixed anomalies in attributed graphs.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Mixedad: A scalable algorithm for detecting mixed anomalies in attributed graphs

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:16:14.396916Z

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Observation 0cf73341-ff69-4e9a-a4b4-878be7babf38 · outbound

This paper cites AliGraph: A Comprehensive Graph Neural Network Platform.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs AliGraph: A Comprehensive Graph Neural Network Platform

Reference 100

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