mlsanityData to 14 Oct 2026

GeniePath: Graph Neural Networks with Adaptive Receptive Paths

arXiv 1802.00910 ↗First posted 3 Feb 2018cs.LGcited by 66

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Abstract (arXiv)

We present, GeniePath, a scalable approach for learning adaptive receptive fields of neural networks defined on permutation invariant graph data. In GeniePath, we propose an adaptive path layer consists of two complementary functions designed for breadth and depth exploration respectively, where the former learns the importance of different sized neighborhoods, while the latter extracts and filters signals aggregated from neighbors of different hops away. Our method works in both transductive and inductive settings, and extensive experiments compared with competitive methods show that our approaches yield state-of-the-art results on large graphs.

Key facts. Cited by 66 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Feb 2018.

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Citing papers per year: 2021: 18; 2022: 13; 2023: 13; 2024: 16; 2025: 2; 2026: 4.

66 papers.

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  1. 2022Graph-Coupled Oscillator Networkscited by 124
  2. 2021PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equationscited by 106
  3. 2021A Review on Graph Neural Network Methods in Financial Applicationscited by 78
  4. 2023GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detectioncited by 58
  5. 2021Search to aggregate neighborhood for graph neural networkcited by 48
  6. 2021Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networkscited by 38
  7. 2021Federated Graph Learning -- A Position Papercited by 35
  8. 2021SPAGAN: Shortest Path Graph Attention Networkcited by 28
  9. 2023Language Knowledge-Assisted Representation Learning for Skeleton-Based Action Recognitioncited by 27
  10. 2021Scalable deeper graph neural networks for high-performance materials property predictioncited by 26
  11. 2021Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting -- Full versioncited by 24
  12. 2021Graph Transformer Networks: Learning Meta-path Graphs to Improve GNNscited by 22
38 more
  1. 2021Graph Contrastive Learning for Anomaly Detectioncited by 22
  2. 2022DAGAD: Data Augmentation for Graph Anomaly Detectioncited by 20
  3. 2022Improving Graph Neural Networks with Learnable Propagation Operatorscited by 19
  4. 2022pathGCN: Learning General Graph Spatial Operators from Pathscited by 15
  5. 2024UniGAD: Unifying Multi-level Graph Anomaly Detectioncited by 14
  6. 2023Cost Sensitive GNN-based Imbalanced Learning for Mobile Social Network Fraud Detectioncited by 12
  7. 2024SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learningcited by 12
  8. 2022From Local to Global: Spectral-Inspired Graph Neural Networkscited by 11
  9. 2021Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graphcited by 9
  10. 2021GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategycited by 8
  11. 2023PathMLP: Smooth Path Towards High-order Homophilycited by 8
  12. 2024Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modelingcited by 8
  13. 2022How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generationcited by 7
  14. 2024Multitask Active Learning for Graph Anomaly Detectioncited by 7
  15. 2024VecAug: Unveiling Camouflaged Frauds with Cohort Augmentation for Enhanced Detectioncited by 7
  16. 2022Not All Neighbors Are Worth Attending to: Graph Selective Attention Networks for Semi-supervised Learningcited by 6
  17. 2023Union Subgraph Neural Networkscited by 6
  18. 2025Improving the Effective Receptive Field of Message-Passing Neural Networkscited by 6
  19. 2021GIPA: General Information Propagation Algorithm for Graph Learningcited by 5
  20. 2022Improving Fraud Detection via Hierarchical Attention-based Graph Neural Networkcited by 5
  21. 2022Modelling graph dynamics in fraud detection with "Attention"cited by 5
  22. 2022Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commercecited by 5
  23. 2023Graph Mining for Cybersecurity: A Surveycited by 5
  24. 2023Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networkscited by 5
  25. 2024Training-free Graph Neural Networks and the Power of Labels as Featurescited by 5
  26. 2021Spectral Transform Forms Scalable Transformercited by 4
  27. 2023InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphscited by 4
  28. 2024Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learningcited by 4
  29. 2021Graph Feature Gating Networkscited by 3
  30. 2023Who Would be Interested in Services? An Entity Graph Learning System for User Targetingcited by 3
  31. 2024DiRW: Path-Aware Digraph Learning for Heterophilycited by 3
  32. 2024Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modelingcited by 2
  33. 2024P4GCN: Vertical Federated Social Recommendation with Privacy-Preserving Two-Party Graph Convolution Networkcited by 2
  34. 2021Multimodal and Contrastive Learning for Click Fraud Detectioncited by 1
  35. 2022Self-supervised Graph Representation Learning for Black Market Account Detectioncited by 1
  36. 2023Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effectscited by 1
  37. 2024GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphscited by 1
  38. 2024Open-World Semi-Supervised Learning for Node Classificationcited by 1

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