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94 results on '"graph structure learning"'

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5. Spatially Informed Graph Structure Learning Extracts Insights from Spatial Transcriptomics.

6. scMGATGRN: a multiview graph attention network–based method for inferring gene regulatory networks from single-cell transcriptomic data.

7. Utilizing correlation in space and time: Anomaly detection for Industrial Internet of Things (IIoT) via spatiotemporal gated graph attention network.

8. Utilizing correlation in space and time: Anomaly detection for Industrial Internet of Things (IIoT) via spatiotemporal gated graph attention network

9. Spatially Informed Graph Structure Learning Extracts Insights from Spatial Transcriptomics

11. Spatiotemporal Dynamic Multi-Hop Network for Traffic Flow Forecasting.

12. SGK-Net: A Novel Navigation Scene Graph Generation Network.

13. MSGNN: Multi-scale Spatio-temporal Graph Neural Network for epidemic forecasting.

14. MASMDDI: multi-layer adaptive soft-mask graph neural network for drug-drug interaction prediction.

15. Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution.

16. Graph Transformer Network Incorporating Sparse Representation for Multivariate Time Series Anomaly Detection.

17. A Structure-Enhanced Heterogeneous Graph Representation Learning with Attention-Supplemented Embedding Fusion.

18. Ultra-Short-Term Power Prediction of Large Offshore Wind Farms Based on Spatiotemporal Adaptation of Wind Turbines.

19. A novel autism spectrum disorder identification method: spectral graph network with brain-population graph structure joint learning.

20. AMGCN: adaptive multigraph convolutional networks for traffic speed forecasting.

21. Attentive graph structure learning embedded in deep spatial-temporal graph neural network for traffic forecasting.

22. Health insurance fraud detection based on multi-channel heterogeneous graph structure learning

23. Multikernel Graph Structure Learning for Multispectral Point Cloud Classification

24. Learnable Brain Connectivity Structures for Identifying Neurological Disorders

25. Survey of Research on Personalized News Recommendation Approaches

26. Graph Neural Network-Based Short‑Term Load Forecasting with Temporal Convolution

27. A Survey of Personalized News Recommendation

28. Learnable Brain Connectivity Structures for Identifying Neurological Disorders.

29. Multi-node system modeling and monitoring with extended directed graphical models.

30. A Survey of Personalized News Recommendation.

31. 个性化新闻推荐方法研究综述.

32. Self-supervised robust Graph Neural Networks against noisy graphs and noisy labels.

35. SGK-Net: A Novel Navigation Scene Graph Generation Network

36. Unsupervised Graph Structure Learning Based on Optimal Graph Topology Modeling and Adaptive Data Augmentation

37. Long-tailed graph neural networks via graph structure learning for node classification.

38. Patient multi-relational graph structure learning for diabetes clinical assistant diagnosis

39. A Joint-Learning-Based Dynamic Graph Learning Framework for Structured Prediction †.

40. Adaptive Graph-Learning Convolutional Network for Multi-Node Offshore Wind Speed Forecasting.

41. Time-lagged relation graph neural network for multivariate time series forecasting.

42. Unified node, edge and motif learning networks for graphs.

43. Physics-informed gated recurrent graph attention unit network for anomaly detection in industrial cyber-physical systems.

44. Generic Structure Extraction with Bi-Level Optimization for Graph Structure Learning.

45. Multiplex graph fusion network with reinforcement structure learning for fraud detection in online e-commerce platforms.

46. Time Series Prediction of Sea Surface Temperature Based on an Adaptive Graph Learning Neural Model.

47. TimeGNN: Temporal Dynamic Graph Learning for Time Series Forecasting

48. Adaptive Graph-Learning Convolutional Network for Multi-Node Offshore Wind Speed Forecasting

49. Multimodal graph learning based on 3D Haar semi-tight framelet for student engagement prediction.

50. Spatio-temporal Fourier enhanced heterogeneous graph learning for traffic forecasting.

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