Motivated by dataset distillation (Wang et al., 2018) and dataset condensation (Zhao et al., 2021) which generate a small set of images to train deep neural networks on the downstream task, we aim to condense a given graph through learning a synthetic graph structure and node attributes. 受...
Graph Anomaly Detection with Graph Neural Networks: Current Status and Challenges[J]. IEEE Access, 2022. 团队主要是韩国的IEEE Access, h-index:56, CiteScore:6.70 Abstract 图异常:是指图中不符合正常模式的图形属性或结构的模式。 解决方法:基于GNN的方法利用关于图形属性(或特征)和/或结构的信息来学习...
Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, and predict synthesis routes of new materials. Graph neural
Scientific discovery in the age of artificial intelligence Hanchen Wang Tianfan Fu Marinka Zitnik Nature (2023) Photon Reconstruction in the Belle II Calorimeter Using Graph Neural Networks F. Wemmer I. Haide R. Volpe Computing and Software for Big Science (2023)Associated...
Graph Neural Networks LabML. https://nn.labml.ai/graphs/index.html (2023).7.LaBonne, M. Graph Attention Networks: Theoretical and Practical Insights https : / / mlabonne . github.io/blog/posts/2022-03-09-graph_attention_net...
long-range-dependencegraph-representation-learninggraph-neural-networkgraph-transformer UpdatedJul 4, 2024 Python Shen-Lab/GraphCL Star551 Code Issues Pull requests [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, ...
Graph Neural Networks 通过上面的描述，graph可以通过置换不变的邻接表表示，那么可以设计一个graph neura...
2.3.2 Non-local Neural Networks NLNN是一类自注意力类型的框架。 Wang X, Girshick R, Gupta A, et al. Non-local neural networks[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 7794-7803. NLNN的核心是非局部(non-local)操作,它是对所有位置特征的加权求和...
例如卷积神经网络(Convolutional Neural Networks)可以利用平移不变性、局部连通性和图像数据语意合成性,从而提取出与整个数据集共享的局部有意义的特征,用于各种图像分析任务。 深度神经网络的最新进展推进了模式识别和数据挖掘领域的研究。目标检测、机器翻译、语音识别等许多机器学习任务曾高度依赖手工特征工程来提取信息...
1、GNN Explainer: Generating Explanations for Graph Neural Networks 作者:Zhitao Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec 推荐理由:本文由斯坦福Jure组收录在NeurIPS2019上。神经网络包括图神经网络在很多领...