Graph Neural Networks Applications Across Domains: All Insights You Need | Paper Citation Record

Observation 37b9a061-a0a0-4676-830f-dd2fbabf0a4e · outbound

This paper cites A Deep Learning Approach to Antibiotic Discovery,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Deep Learning Approach to Antibiotic Discovery,

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This paper cites Learning Skillful Medium-Range Global Weather Forecasting,.

Graph Neural Networks Applications Across Domains: All Insights You Need Learning Skillful Medium-Range Global Weather Forecasting,

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This paper cites A Comprehensive Survey on Graph Neural Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Comprehensive Survey on Graph Neural Networks,

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This paper cites Graph Neural Networks: A Review of Methods and Applications,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Neural Networks: A Review of Methods and Applications,

Reference 4

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This paper cites Deep Learning on Graphs: A Survey,.

Graph Neural Networks Applications Across Domains: All Insights You Need Deep Learning on Graphs: A Survey,

Reference 5

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This paper cites Machine Learning on Graphs: A Model and Comprehensive Taxonomy,.

Graph Neural Networks Applications Across Domains: All Insights You Need Machine Learning on Graphs: A Model and Comprehensive Taxonomy,

Reference 6

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This paper cites Graph Convolutional Networks: A Comprehensive Review,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Convolutional Networks: A Comprehensive Review,

Reference 7

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This paper cites Representation Learning on Graphs: Methods and Applications,.

Graph Neural Networks Applications Across Domains: All Insights You Need Representation Learning on Graphs: Methods and Applications,

Reference 8

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This paper cites Geometric Deep Learning: Going Beyond Euclidean Data,.

Graph Neural Networks Applications Across Domains: All Insights You Need Geometric Deep Learning: Going Beyond Euclidean Data,

Reference 9

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This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges,.

Graph Neural Networks Applications Across Domains: All Insights You Need Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges,

Reference 10

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This paper cites Everything is Connected: Graph Neural Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Everything is Connected: Graph Neural Networks,

Reference 11

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This paper cites Graph Neural Networks in Recommender Systems: A Survey,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Neural Networks in Recommender Systems: A Survey,

Reference 12

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This paper cites A Survey on Knowledge Graphs: Representation, Acquisition, and Applications,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Survey on Knowledge Graphs: Representation, Acquisition, and Applications,

Reference 13

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This paper cites A Compact Review of Molecular Property Prediction with Graph Neural Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Compact Review of Molecular Property Prediction with Graph Neural Networks,

Reference 14

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This paper cites Graph Neural Network for Traffic Forecasting: A Survey,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Neural Network for Traffic Forecasting: A Survey,

Reference 15

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This paper cites A Review of Graph Neural Networks and Their Applications in Power Systems,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Review of Graph Neural Networks and Their Applications in Power Systems,

Reference 16

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Graph Neural Networks Applications Across Domains: All Insights You Need Unresolved cited work

Reference 17

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This paper cites A Survey on the Expressive Power of Graph Neural Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Survey on the Expressive Power of Graph Neural Networks,

Reference 18

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This paper cites Weisfeiler and Leman Go Machine Learning: The Story So Far,.

Graph Neural Networks Applications Across Domains: All Insights You Need Weisfeiler and Leman Go Machine Learning: The Story So Far,

Reference 19

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This paper cites Self-Supervised Learning on Graphs: Contrastive, Generative, or Predictive,.

Graph Neural Networks Applications Across Domains: All Insights You Need Self-Supervised Learning on Graphs: Contrastive, Generative, or Predictive,

Reference 20

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This paper cites Self-Supervised Learning of Graph Neural Networks: A Unified Review,.

Graph Neural Networks Applications Across Domains: All Insights You Need Self-Supervised Learning of Graph Neural Networks: A Unified Review,

Reference 21

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This paper cites Representation Learning for Dynamic Graphs: A Survey,.

Graph Neural Networks Applications Across Domains: All Insights You Need Representation Learning for Dynamic Graphs: A Survey,

Reference 22

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This paper cites A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources,

Reference 23

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This paper cites A Comprehensive Survey of Graph Neural Networks for Knowledge Graphs,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Comprehensive Survey of Graph Neural Networks for Knowledge Graphs,

Reference 24

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This paper cites Graph Convolutional Networks for Computational Drug Development and Discovery,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Convolutional Networks for Computational Drug Development and Discovery,

Reference 25

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This paper cites A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection,

Reference 26

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This paper cites Graph Neural Networks for Wireless Communications: From Theory to Practice,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Neural Networks for Wireless Communications: From Theory to Practice,

Reference 27

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

Graph Neural Networks Applications Across Domains: All Insights You Need A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability,

Reference 28

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This paper cites Bench- marking Graph Neural Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Bench- marking Graph Neural Networks,

Reference 29

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This paper cites Open Graph Benchmark: Datasets for Machine Learning on Graphs,.

Graph Neural Networks Applications Across Domains: All Insights You Need Open Graph Benchmark: Datasets for Machine Learning on Graphs,

Reference 30

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This paper cites Simplifying Graph Convolutional Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Simplifying Graph Convolutional Networks,

Reference 31

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This paper cites Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs,.

Graph Neural Networks Applications Across Domains: All Insights You Need Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs,

Reference 32

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This paper cites Geom-GCN: Geometric Graph Convolutional Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Geom-GCN: Geometric Graph Convolutional Networks,

Reference 33

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This paper cites Inductive Representation Learning on Large Graphs,.

Graph Neural Networks Applications Across Domains: All Insights You Need Inductive Representation Learning on Large Graphs,

Reference 34

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This paper cites Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks,

Reference 35

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This paper cites Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey,.

Graph Neural Networks Applications Across Domains: All Insights You Need Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey,

Reference 36

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This paper cites How Powerful are Graph Neural Networks?.

Graph Neural Networks Applications Across Domains: All Insights You Need How Powerful are Graph Neural Networks?

Reference 37

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Graph Neural Networks Applications Across Domains: All Insights You Need Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks,

Reference 38

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This paper cites Explainability in Graph Neural Networks: A Taxonomic Survey,.

Graph Neural Networks Applications Across Domains: All Insights You Need Explainability in Graph Neural Networks: A Taxonomic Survey,

Reference 39

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This paper cites Towards Graph Foundation Models: A Survey and Beyond,.

Graph Neural Networks Applications Across Domains: All Insights You Need Towards Graph Foundation Models: A Survey and Beyond,

Reference 40

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Graph Neural Networks Applications Across Domains: All Insights You Need Position: Graph Foundation Models Are Already Here,

Reference 41

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This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization,.

Graph Neural Networks Applications Across Domains: All Insights You Need From Local to Global: A Graph RAG Approach to Query-Focused Summarization,

Reference 42

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This paper cites Large Language Models on Graphs: A Comprehensive Survey,.

Graph Neural Networks Applications Across Domains: All Insights You Need Large Language Models on Graphs: A Comprehensive Survey,

Reference 43

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This paper cites One for All: Towards Training One Graph Model for All Classification Tasks,.

Graph Neural Networks Applications Across Domains: All Insights You Need One for All: Towards Training One Graph Model for All Classification Tasks,

Reference 44

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This paper cites Towards Foundation Models for Knowledge Graph Reasoning,.

Graph Neural Networks Applications Across Domains: All Insights You Need Towards Foundation Models for Knowledge Graph Reasoning,

Reference 45

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This paper cites A New Model for Learning in Graph Domains,.

Graph Neural Networks Applications Across Domains: All Insights You Need A New Model for Learning in Graph Domains,

Reference 46

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This paper cites The Graph Neural Network Model,.

Graph Neural Networks Applications Across Domains: All Insights You Need The Graph Neural Network Model,

Reference 47

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This paper cites Spectral Networks and Locally Connected Networks on Graphs,.

Graph Neural Networks Applications Across Domains: All Insights You Need Spectral Networks and Locally Connected Networks on Graphs,

Reference 48

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This paper cites Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering,.

Graph Neural Networks Applications Across Domains: All Insights You Need Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering,

Reference 49

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This paper cites Semi-Supervised Classification with Graph Convolutional Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Semi-Supervised Classification with Graph Convolutional Networks,

Reference 50

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This paper cites Graph Attention Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Attention Networks,

Reference 51

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This paper cites Neural Message Passing for Quantum Chemistry,.

Graph Neural Networks Applications Across Domains: All Insights You Need Neural Message Passing for Quantum Chemistry,

Reference 52

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This paper cites Do Transformers Really Perform Bad for Graph Representation?.

Graph Neural Networks Applications Across Domains: All Insights You Need Do Transformers Really Perform Bad for Graph Representation?

Reference 53

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This paper cites Relational Inductive Biases, Deep Learning, and Graph Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Relational Inductive Biases, Deep Learning, and Graph Networks,

Reference 54

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This paper cites A Survey of Large Language Models for Graphs,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Survey of Large Language Models for Graphs,

Reference 55

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This paper cites Graph Retrieval-Augmented Generation: A Survey,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Retrieval-Augmented Generation: A Survey,

Reference 56

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This paper cites Adversarial Attack and Defense on Graph Data: A Survey,.

Graph Neural Networks Applications Across Domains: All Insights You Need Adversarial Attack and Defense on Graph Data: A Survey,

Reference 57

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This paper cites MoleculeNet: A Benchmark for Molecular Machine Learning,.

Graph Neural Networks Applications Across Domains: All Insights You Need MoleculeNet: A Benchmark for Molecular Machine Learning,

Reference 58

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This paper cites Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs,.

Graph Neural Networks Applications Across Domains: All Insights You Need Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs,

Reference 59

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This paper cites Diffusion-Convolutional Neural Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Diffusion-Convolutional Neural Networks,

Reference 60

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This paper cites Learning Convolutional Neural Networks for Graphs,.

Graph Neural Networks Applications Across Domains: All Insights You Need Learning Convolutional Neural Networks for Graphs,

Reference 61

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This paper cites FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling,.

Graph Neural Networks Applications Across Domains: All Insights You Need FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling,

Reference 62

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This paper cites GraphSAINT: Graph Sampling Based Inductive Learning Method,.

Graph Neural Networks Applications Across Domains: All Insights You Need GraphSAINT: Graph Sampling Based Inductive Learning Method,

Reference 63

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Observation e45b8045-c5e2-4ef5-94b5-56e837decb6d · outbound

This paper cites Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs,.

Graph Neural Networks Applications Across Domains: All Insights You Need Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs,

Reference 64

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Observation d8e51dc4-4213-4b23-8829-1d51fac24ac7 · outbound

This paper cites Residual Gated Graph ConvNets,.

Graph Neural Networks Applications Across Domains: All Insights You Need Residual Gated Graph ConvNets,

Reference 65

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Observation 29175770-bf31-44d8-bd36-5258af3f94c4 · outbound

This paper cites E(n) Equivariant Graph Neural Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need E(n) Equivariant Graph Neural Networks,

Reference 66

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Observation a2893a45-562d-4c14-9e58-4731817e934a · outbound

This paper cites Principal Neighbourhood Aggregation for Graph Nets,.

Graph Neural Networks Applications Across Domains: All Insights You Need Principal Neighbourhood Aggregation for Graph Nets,

Reference 67

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Observation 76ddd1dd-66f5-4ddc-9bca-00883811157c · outbound

This paper cites Position: Future Directions in the Theory of Graph Machine Learning,.

Graph Neural Networks Applications Across Domains: All Insights You Need Position: Future Directions in the Theory of Graph Machine Learning,

Reference 68

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Observation 2c1def68-26ea-4c89-8226-d69905f2d9a9 · outbound

This paper cites Graph Neural Networks Exponentially Lose Expressive Power for Node Classification,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Neural Networks Exponentially Lose Expressive Power for Node Classification,

Reference 69

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Observation 63ecb2c8-e762-40f5-a2f0-ed22840d9397 · outbound

This paper cites Representation Learning on Graphs with Jumping Knowledge Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Representation Learning on Graphs with Jumping Knowledge Networks,

Reference 70

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Observation 56c48f47-5474-4590-bd97-56329d0d65e1 · outbound

This paper cites Predict then Propagate: Graph Neu- ral Networks meet Personalized PageRank,.

Graph Neural Networks Applications Across Domains: All Insights You Need Predict then Propagate: Graph Neu- ral Networks meet Personalized PageRank,

Reference 71

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Observation 75f763a7-3d00-4142-8d6d-582e28f26056 · outbound

This paper cites Simple and Deep Graph Convolutional Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Simple and Deep Graph Convolutional Networks,

Reference 72

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation bd1c9007-584e-4c21-92d5-975713320ceb · outbound

This paper cites DropEdge: Towards Deep Graph Convolutional Networks on Node Classification,.

Graph Neural Networks Applications Across Domains: All Insights You Need DropEdge: Towards Deep Graph Convolutional Networks on Node Classification,

Reference 73

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Observation cea29253-2222-409c-b971-275bac0ca464 · outbound

This paper cites PairNorm: Tackling Oversmoothing in GNNs,.

Graph Neural Networks Applications Across Domains: All Insights You Need PairNorm: Tackling Oversmoothing in GNNs,

Reference 74

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation f107109b-377c-4d13-a1dc-95ed17ecf9a4 · outbound

This paper cites A Generalization of Transformer Networks to Graphs,.

Graph Neural Networks Applications Across Domains: All Insights You Need A Generalization of Transformer Networks to Graphs,

Reference 75

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation f0a6ac31-15dc-4605-a2a7-3099d18e9e5e · outbound

This paper cites Rethinking Graph Transformers with Spectral Attention,.

Graph Neural Networks Applications Across Domains: All Insights You Need Rethinking Graph Transformers with Spectral Attention,

Reference 76

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Graph Neural Networks Applications Across Domains: All Insights You Need Recipe for a General, Powerful, Scalable Graph Transformer,

Reference 77

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This paper cites Structure-Aware Transformer for Graph Repre- sentation Learning,.

Graph Neural Networks Applications Across Domains: All Insights You Need Structure-Aware Transformer for Graph Repre- sentation Learning,

Reference 78

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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This paper cites Pure Transformers are Powerful Graph Learners,.

Graph Neural Networks Applications Across Domains: All Insights You Need Pure Transformers are Powerful Graph Learners,

Reference 79

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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This paper cites Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting,.

Graph Neural Networks Applications Across Domains: All Insights You Need Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting,

Reference 80

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation b00281c7-6c14-4184-b9f1-55cf2e615cb5 · outbound

This paper cites Trustworthy Graph Neural Networks: Aspects, Methods, and Trends,.

Graph Neural Networks Applications Across Domains: All Insights You Need Trustworthy Graph Neural Networks: Aspects, Methods, and Trends,

Reference 81

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation 2dd2ccdc-e7e7-46c4-a976-59ed8627042a · outbound

This paper cites Evolving Beyond Snapshots: Harmonizing Structure and Sequence via Entity State Tuning for Temporal Knowledge Graph Forecasting,.

Graph Neural Networks Applications Across Domains: All Insights You Need Evolving Beyond Snapshots: Harmonizing Structure and Sequence via Entity State Tuning for Temporal Knowledge Graph Forecasting,

Reference 82

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Observation a9d0f4fe-8649-4797-9b40-072e45114711 · outbound

This paper cites Modeling Relational Data with Graph Convolutional Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Modeling Relational Data with Graph Convolutional Networks,

Reference 83

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation a2142ddf-62d0-48a4-9396-356691ccd212 · outbound

This paper cites Heterogeneous Graph Attention Network,.

Graph Neural Networks Applications Across Domains: All Insights You Need Heterogeneous Graph Attention Network,

Reference 84

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation 83754379-741b-487d-bfc7-f99ebea4236c · outbound

This paper cites Composition-Based Multi-Relational Graph Convolutional Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Composition-Based Multi-Relational Graph Convolutional Networks,

Reference 85

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Observation c6df8850-65c1-4ad3-93e6-71c4cab0d95c · outbound

This paper cites Hierarchical Graph Representation Learning with Differentiable Pooling,.

Graph Neural Networks Applications Across Domains: All Insights You Need Hierarchical Graph Representation Learning with Differentiable Pooling,

Reference 86

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Observation 565d98e4-57c3-44c8-a900-2833bdbced94 · outbound

This paper cites Self-Attention Graph Pooling,.

Graph Neural Networks Applications Across Domains: All Insights You Need Self-Attention Graph Pooling,

Reference 87

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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This paper cites Graph U-Nets,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph U-Nets,

Reference 88

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation b443bf4b-e9f3-436c-bd5e-0050d427391d · outbound

This paper cites Spectral Clustering with Graph Neural Networks for Graph Pooling,.

Graph Neural Networks Applications Across Domains: All Insights You Need Spectral Clustering with Graph Neural Networks for Graph Pooling,

Reference 89

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation 732e4a06-bc5d-40d0-8884-dc97b2fa50d8 · outbound

This paper cites Deep Graph Infomax,.

Graph Neural Networks Applications Across Domains: All Insights You Need Deep Graph Infomax,

Reference 90

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation a2202be0-b6b4-4062-b386-7feb8c5f2251 · outbound

This paper cites Graph Contrastive Learning with Augmentations,.

Graph Neural Networks Applications Across Domains: All Insights You Need Graph Contrastive Learning with Augmentations,

Reference 91

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Observation c454b99e-54fc-4d31-87b4-d5cb31ef86d1 · outbound

This paper cites DeepGraphContrastiveRepresentation Learning,.

Graph Neural Networks Applications Across Domains: All Insights You Need DeepGraphContrastiveRepresentation Learning,

Reference 92

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation 98511fd5-270d-4a88-b62d-0df67654707e · outbound

This paper cites Contrastive Multi-View Representation Learning on Graphs,.

Graph Neural Networks Applications Across Domains: All Insights You Need Contrastive Multi-View Representation Learning on Graphs,

Reference 93

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation 298c1240-3ebc-41d8-99fb-f14be340c802 · outbound

This paper cites Large-Scale Representation Learning on Graphs via Bootstrapping,.

Graph Neural Networks Applications Across Domains: All Insights You Need Large-Scale Representation Learning on Graphs via Bootstrapping,

Reference 94

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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This paper cites GraphMAE: Self- Supervised Masked Graph Autoencoders,.

Graph Neural Networks Applications Across Domains: All Insights You Need GraphMAE: Self- Supervised Masked Graph Autoencoders,

Reference 95

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Observation b6f227f3-c5de-4461-86f1-478de667bcec · outbound

This paper cites StrategiesforPre- training Graph Neural Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need StrategiesforPre- training Graph Neural Networks,

Reference 96

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This paper cites GPT-GNN: Generative Pre-Training of Graph Neural Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need GPT-GNN: Generative Pre-Training of Graph Neural Networks,

Reference 97

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Observation e3a9c803-8ae8-4fb5-b14b-55de6b73ec50 · outbound

This paper cites GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training,.

Graph Neural Networks Applications Across Domains: All Insights You Need GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training,

Reference 98

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation 8ab01a62-ff5a-4e9b-a717-14f42b3dc1d8 · outbound

This paper cites InfoGraph: Unsupervised and Semi- Supervised Graph-Level Representation Learning via Mutual Information Maximization,.

Graph Neural Networks Applications Across Domains: All Insights You Need InfoGraph: Unsupervised and Semi- Supervised Graph-Level Representation Learning via Mutual Information Maximization,

Reference 99

Resolution: unresolved; no resolver link, observed 2026-06-26T04:53:15.929349Z

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Observation 5b34d88a-5403-4357-ba79-7df36ba79eaa · outbound

This paper cites Signed Graph Convolutional Networks,.

Graph Neural Networks Applications Across Domains: All Insights You Need Signed Graph Convolutional Networks,

Reference 100

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