mlsanityData to 7 Oct 2026

Dynamic Graph Convolutional Networks

arXiv 1704.06199 ↗First posted 20 Apr 2017cs.LG stat.MLcited by 83

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Abstract (arXiv)

Many different classification tasks need to manage structured data, which are usually modeled as graphs. Moreover, these graphs can be dynamic, meaning that the vertices/edges of each graph may change during time. Our goal is to jointly exploit structured data and temporal information through the use of a neural network model. To the best of our knowledge, this task has not been addressed using these kind of architectures. For this reason, we propose two novel approaches, which combine Long Short-Term Memory networks and Graph Convolutional Networks to learn long short-term dependencies together with graph structure. The quality of our methods is confirmed by the promising results achieved.

Key facts. Cited by 83 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Apr 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 19; 2022: 14; 2023: 14; 2024: 17; 2025: 13; 2026: 6.

83 papers.

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  1. 2021Inductive Representation Learning in Temporal Networks via Causal Anonymous Walkscited by 188
  2. 2021SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequencescited by 159
  3. 2021Graph Learning: A Surveycited by 140
  4. 2022Provably expressive temporal graph networkscited by 56
  5. 2022Neighborhood-aware Scalable Temporal Network Representation Learningcited by 54
  6. 2024A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challengescited by 29
  7. 2023Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalizationcited by 26
  8. 2022Graph Neural Networks Designed for Different Graph Types: A Surveycited by 21
  9. 2024A survey of dynamic graph neural networkscited by 21
  10. 2023Embedding in Recommender Systems: A Surveycited by 19
  11. 2023GraphPro: Graph Pre-training and Prompt Learning for Recommendationcited by 17
  12. 2022Time-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphscited by 16
38 more
  1. 2022Instant Graph Neural Networks for Dynamic Graphscited by 16
  2. 2023Dynamic Graph Representation Learning with Neural Networks: A Surveycited by 15
  3. 2022Encoder-Decoder Architecture for Supervised Dynamic Graph Learning: A Surveycited by 14
  4. 2023Decoupled Graph Neural Networks for Large Dynamic Graphscited by 14
  5. 2021Neural Predicting Higher-order Patterns in Temporal Networkscited by 13
  6. 2021Efficient Scaling of Dynamic Graph Neural Networkscited by 11
  7. 2021Lifelong Learning on Evolving Graphs Under the Constraints of Imbalanced Classes and New Classescited by 11
  8. 2021On the Equivalence Between Temporal and Static Graph Representations for Observational Predictionscited by 10
  9. 2022Graph-Time Convolutional Neural Networks: Architecture and Theoretical Analysiscited by 10
  10. 2022Learnable Spectral Wavelets on Dynamic Graphs to Capture Global Interactionscited by 10
  11. 2026A Novel Approach to Temporal QoS Estimation via Extended Kalman Filter-Incorporated Latent Feature Analysiscited by 9
  12. 2021Graph-Time Convolutional Neural Networkscited by 8
  13. 2021Temporal Graph Signal Decompositioncited by 8
  14. 2022Time-aware Dynamic Graph Embedding for Asynchronous Structural Evolutioncited by 8
  15. 2024Tensor Graph Convolutional Network for Dynamic Graph Representation Learningcited by 8
  16. 2021Representing Shape Collections with Alignment-Aware Linear Modelscited by 7
  17. 2021Revisiting Latent-Space Interpolation via a Quantitative Evaluation Frameworkcited by 7
  18. 2024Towards Continuous Reuse of Graph Models via Holistic Memory Diversificationcited by 7
  19. 2021DyGCN: Dynamic Graph Embedding with Graph Convolutional Networkcited by 6
  20. 2024Attention-based Dynamic Multilayer Graph Neural Networks for Loan Default Predictioncited by 5
  21. 2025TIDFormer: Exploiting Temporal and Interactive Dynamics Makes A Great Dynamic Graph Transformercited by 5
  22. 2021Spectral Transform Forms Scalable Transformercited by 4
  23. 2022Graph similarity learning for change-point detection in dynamic networkscited by 4
  24. 2024Machine Learning on Dynamic Graphs: A Survey on Applicationscited by 4
  25. 2021Radflow: A Recurrent, Aggregated, and Decomposable Model for Networks of Time Seriescited by 3
  26. 2022Dynamic Graph Node Classification via Time Augmentationcited by 3
  27. 2023DGNN-Booster: A Generic FPGA Accelerator Framework For Dynamic Graph Neural Network Inferencecited by 3
  28. 2023H2CGL: Modeling Dynamics of Citation Network for Impact Predictioncited by 3
  29. 2023GTNet: Graph Transformer Network for 3D Point Cloud Classification and Semantic Segmentationcited by 3
  30. 2024Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphscited by 3
  31. 2026Evaluating Progress in Graph Foundation Models: A Comprehensive Benchmark and New Insightscited by 3
  32. 2021Temporal Graph Network Embedding with Causal Anonymous Walks Representationscited by 2
  33. 2021Learning to Evolve on Dynamic Graphscited by 2
  34. 2022Search to Pass Messages for Temporal Knowledge Graph Completioncited by 2
  35. 2023Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphscited by 2
  36. 2024Node Classification via Semantic-Structural Attention-Enhanced Graph Convolutional Networkscited by 2
  37. 2024ModeConv: A Novel Convolution for Distinguishing Anomalous and Normal Structural Behaviorcited by 2
  38. 2024Graph Retention Networks for Dynamic Graphscited by 2

50 most cited of 83 All 83 (JSON)