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188 results on '"graph contrastive learning"'

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20. Simplify to the Limit! Embedding-Less Graph Collaborative Filtering for Recommender Systems.

21. Predicting noncoding RNA and disease associations using multigraph contrastive learning.

22. 结合图神经网络和图对比学习的半监督多图分类.

23. GPS: graph contrastive learning via multi-scale augmented views from adversarial pooling.

24. Spoken language understanding via graph contrastive learning on the context-aware graph convolutional network.

25. DAPNet: multi-view graph contrastive network incorporating disease clinical and molecular associations for disease progression prediction.

26. A novel multi-view contrastive learning for herb recommendation.

27. GGN-GO: geometric graph networks for predicting protein function by multi-scale structure features.

28. Graph contrastive learning as a versatile foundation for advanced scRNA-seq data analysis.

29. XsimGCL's cross-layer for group recommendation using extremely simple graph contrastive learning.

30. Position-Aware and Subgraph Enhanced Dynamic Graph Contrastive Learning on Discrete-Time Dynamic Graph.

31. Graph Contrastive Pre-training for Anti-money Laundering

32. Harnessing Unsupervised Insights: Enhancing Black-Box Graph Injection Attacks with Graph Contrastive Learning.

33. Heterogeneous Graph Contrastive Learning with Attention Mechanism for Recommendation.

34. Joint data augmentations for automated graph contrastive learning and forecasting.

35. A Recommendation System for Trigger–Action Programming Rules via Graph Contrastive Learning.

36. Global-local aware Heterogeneous Graph Contrastive Learning for multifaceted association prediction in miRNA–gene–disease networks.

37. 基于数据与特征增强的自监督图表示学习方法.

38. BotCL: a social bot detection model based on graph contrastive learning.

39. MDGCL: Graph Contrastive Learning Framework with Multiple Graph Diffusion Methods.

40. Towards Robust Rumor Detection with Graph Contrastive and Curriculum Learning.

41. Accurate Spatial Heterogeneity Dissection and Gene Regulation Interpretation for Spatial Transcriptomics using Dual Graph Contrastive Learning

44. Joint data augmentations for automated graph contrastive learning and forecasting

45. Accurately deciphering spatial domains for spatially resolved transcriptomics with stCluster.

46. ProtoMGAE: Prototype-Aware Masked Graph Auto-Encoder for Graph Representation Learning.

47. scZAG: Integrating ZINB-Based Autoencoder with Adaptive Data Augmentation Graph Contrastive Learning for scRNA-seq Clustering.

48. TP-GCL: graph contrastive learning from the tensor perspective.

49. Debiased graph contrastive learning based on positive and unlabeled learning.

50. A Lightweight Method for Graph Neural Networks Based on Knowledge Distillation and Graph Contrastive Learning.