most of them focus on graph representation learning [ 15, 16, 17 ] and little attention has been paid to systematically review graph generation techniques. Two other surveys [ 18 , 19 ] mostly focus on the generation process and generative models while we focus on the entire spectrum of ...
In general cases, it takes thousands of steps for diffusion models to generate a high-quality sample. Mainly focusing on improving sampling speed, many works from different aspects come into reality. Besides, other problems such as variational gap optimization, distribution diversification, and ...
graph diffusion graph sampling 1.2.1 Edge Addition/Dropping 即 保留原始节点顺序,对邻接矩阵种的元进行改写。 基于图稀疏性(graph sparsification)的图结构优化方法 [8、9],基于图结构整洁性(graph sanitation)的方法 [3],以及图采样(graph sampling)。
[1] Zhang H. mixup: Beyond empirical risk minimization[C]//The Sixth International Conference on Learning Representations, 2018. [2] Trabucco B, Doherty K, Gurinas M A, et al. Effective Data Augmentation With Diffusion Models[C]//The Twelfth International Conference on Learning Representations, ...
2023 Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks LoG 2023 Link Link 2023 Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion Models arXiv 2023 Link Link 2023 GAD-NR: Graph Anomaly Detection via Neighborhood ...
图生成网络 Graph Generative Networks 分子生成对抗网络 Molecular Generative Adversarial Networks (MolGAN) Deep Generative Models of Graphs (DGMG) 图时空网络Graph Spatial-Temporal Networks 扩散卷积递归神经网络 Diffusion Convolutional Recurrent Neural Network (DCRNN) ...
By utilizing pairs of diffusion MRI-based structural connectivity matrices as input, this learning strategy effectively enlarged the sample size to alleviate model overfitting and enhance diagnosis accuracy. Despite the promising progress, existing GCN models are limited, as graph edges are fixed during ...
Chen D Y, Tian X P, Shen Y T, Ouhyoung M. On visual similarity based 3D model retrieval. Computer Graphics Forum, 2003, 22(3): 223-232.. Google Scholar [4] Jayanti S, Kalyanaraman Y, Iyer N, Ramani K. Developing an engineering shape benchmark for CAD models. ComputerAided Design...
A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions 3. 快速浏览通道:思维导图 如果看不清楚的话可以去评论区下载源文件~ 1. Intro 1.1 推荐算法发展历史 1.1.1 Shallow Models 协同过滤CF,代表方法矩阵分解MF 《Matrix factorization techniques for recommender systems...
information Review A Survey on Information Diffusion in Online Social Networks: Models and Methods Mei Li *, Xiang Wang, Kai Gao and Shanshan Zhang School of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; wangxiang@hebust.edu.cn (X.W....