网上已有这篇论文的一些讲解,如有讲的不清楚的地方,可移至其他博客。 持续更新中--- Title: Self supervised graph neural network for improving electroencephalographic analysis 作者:Siyi Tang, …
We present InfoMotif, a new semi-supervised, motif-regularized, learning framework over graphs. We overcome two key limitations of message passing in popular graph neural networks (GNNs): localization (a k-layer GNN cannot utilize features outside the k-hop neighborhood of the labeled training ...
Tang, “Infograph: Unsupervised and semi-supervised graphlevel representation learning via mutual information maximization,” arXiv preprint arXiv:1908.01000, 2019. [7] F. Manessi and A. Rozza, “Graph-based neural network models with multiple self-supervised auxiliary tasks,” arXiv preprint arXiv...
3.节点表示容易收到噪声交互的影响。在本文中作者通过在用户-物品图上引入自监督学习来改善GCN在推荐系统上的准确率和鲁棒性,将其称为Self-supervised Graph Learning(SGL),并应用在LightGCN模型上。SGL是模型无关的,并通过辅助自监督任务来补充监督任务中的信息以达成上述目的。
https://github.com/LirongWu/awesome-graph-self-supervised-learning 近些年来,图上的深度学习在各种任务上取得了显著的成功,而这种成功在很大程度上依赖于海量的、精心标注的数据。然而,精确的标注通常非常昂贵和耗时。为了解决这个问题,自监督学习(Self-supervised Learning,SSL)正在成为一种全新的范式,通过精心设计的...
Graph Self-Supervised Learning: A Survey 作者:Philip S. Yu等 主要工作: 对图自监督学习进行归类 总结了已有的图自监督学习的工作 提出了对后续的图自监督学习工作方向的展望 相较于已有的图自监督学习综述,他们的工作对这块分得更科学更细致 Introduction 部分 ...
[arXiv 2023] Structure-Aware Group Discrimination with Adaptive-View Graph Encoder: A Fast Graph Contrastive Learning Framework [paper] [TNNLS 2023] Self-supervised Learning IoT Device Features with Graph Contrastive Neural Network for Device Classification in Social Internet of Things [paper] [TKDE ...
Recently, pretraining methods for the Graph Neural Networks (GNNs) have been successful at learning effective representations from unlabeled graph data. However, most of these methods rely on pairwise relations in the graph and do not capture the underling higher-order relations between entities. Hyp...
deep-learningscalabilitylink-predictionself-supervisiongraph-neural-networksself-supervised-learninggnnefficient-trainingnon-contrastive-learning UpdatedJan 13, 2023 Python Self-Supervised RGBD Reconstruction from Brain Activity image-reconstructionfmridepth-estimationmind-readingself-supervisionbrain-decoding ...
Graph Comparative Learning (GCL) is a self-supervised method that combines the advantages of Graph Convolutional Networks (GCNs) and comparative learning, making it promising for learning node representations. However, the GCN encoders used in these methods rely on the Fourier transform to learn fixe...