Continuous-Time Dynamic Graph (CTDG) precisely models evolving real-world relationships, drawing heightened interest in dynamic graph learning across academia and industry. However, existing CTDG models encounter challenges stemming from noise and limited historical data. Graph Data Augmentation (GDA) emerge...
At the same time, due to the lack of appropriate data augmentation methods, it is difficult to capture the evolving patterns of the network effectively. To address the above problems, a position-aware and subgraph enhanced dynamic graph contrastive learning method is proposed for discrete-time ...
ConDGAD first converts the multivariate time series data into dynamic graphs. Then multiple graph augmentations are performed and a novel contrastive learning process is applied on the dynamic graphs. This enable to train a model that can effectively capture the graph dynamics and perform accurate ...
Adaptive Data Augmentation on Temporal Graphs (Neurips, 2022) [paper] Parameter-free Dynamic Graph Embedding for Link Prediction (Neurips, 2022) [paper][code] Instant Graph Neural Networks for Dynamic Graphs (KDD, 2022) [paper][code] Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overd...
graph approach that is structured into three layers. The first layer represents the real world, where hardware is located and reactions take place. The second layer consists of a dynamic knowledge graph in cyberspace, hosting information such as the digital twin of the hardware and chemical data....
Availability of data and materials The source code and data information is publicly available at https://github.com/Mrfengdashen/DGCPPISP.Abbreviations PPI: Protein–protein interaction RF: Random forest LR: Logistic Regression GAT: Graph attention network PSSM: Position-specific scoring matrix ...
9Weformulateaconvolution-likeoperationongraph 21.Introductionsignalsperformedinthespatialwherefilter 0 .weightsareconditionedonedgelabels(discreteor 4ConvolutionalNeuraworks(CNNs)havegainedcontinuous)anddynamicallygeneratedforeachspe- 0massivepopularityintaskswheretheunderlyingdatarepre-cificinputsample.Ouworkswor...
In recent years, graph/hypergraph-based deep learning methods have attracted much attention from researchers. These deep learning methods take graph/hypergraph structure as prior knowledge in the model. However, hidden and important relations are not directly represented in the inherent structure. To ta...
Define dynamicists. dynamicists synonyms, dynamicists pronunciation, dynamicists translation, English dictionary definition of dynamicists. n. 1. a. The branch of mechanics that is concerned with the effects of forces on the motion of a body or system of
关键词: KNOWLEDGE graphs DATA augmentation GRAPH neural networks GRAPH labelings ATTENTION DOI: 10.3390/electronics13183594 年份: 2024 收藏 引用 批量引用 报错 分享 全部来源 求助全文 EBSCO mdpi.com 相似文献Social-aware graph contrastive learning for recommender systems Learning the representation of nodes...