EQUIVARIANT AND STABLE POSITIONAL ENCODING FOR MORE POWERFUL GRAPH NEURAL NETWORKS Position-aware graph neural network(desperate) 概述 这篇paper中提到了部分关于节点的position 编码的方法,这篇文章的详细介绍可见下,这里主要关注position encoding for gnn。 Mark:图神经网络的新基准Benchmarking Graph Neural Netwo...
In this\npaper,we develop GraphReach, a position-aware inductive GNN that captures the\nglobal positions of nodes through reachability estimations with respect to a\nset of anchor nodes. The anchors are strategically selected so that\nreachability estimations across all the nodes are maximized. We...
11. The scenario considered here is that any authorized wireless roaming node among the seven nodes shown in the graph (see Fig. 11) may broadcast the authentication message to authorized nodes of a specific least cloaked area and hence confidentiality can be achieved in terms of forwarding the...
Traffic accident prediction is crucial for enhancing road safety and mitigating congestion, and recent Graph Neural Networks (GNNs) have shown promise in m... Jiang, Xiangyu,Chen, Xiwen,Wang, Hao,... 被引量: 0发表: 2024年 Aspect-Based Sentiment Analysis with Position Embedding Interactive Attent...
The requirements of location-aware networks and technologies are driven by applications. Since the measurements used to estimate the agent's position are affected by some uncertainty (e.g., noise), the agent's position estimate will also be characterized by errors. ...
We describe an efficient implementation of our method and cast it as an instance of relation-aware self-attention mechanisms that can generalize to arbitrary graph-labeled inputs. 展开 关键词: Computer Science - Computation and Language 会议名称: Proceedings of the 2018 Conference of the North ...
instanceofrelation-awareself-attentionmech-anismsthatcangeneralizetoarbitrarygraph-labeledinputs.1IntroductionRecentapproachestosequencetosequencelearn-ingtypicallyleveragerecurrence(Sutskeveretal.,2014),convolution(Gehringetal.,2017;Kalch-brenneretal.,2016),attention(Vaswanietal.,2017),oracombinationofrecurrenceand...
为捕结构角度的空间依赖关系来提升 GNN 的表征能力,本文提出 Position-aware Graph Neural Networks (P-GNNs),通过建模当前节点对于全局其他节点的位置信息完成节点嵌入。其背后的直觉是,P-GNNs 可以通过量化当前节点和一组锚节点之间的距离将节点位置信息表示为低失真的嵌入。基于 message-passing 的 GNN 可以看作是...
Entity-relationship extraction is a fine-grained task for constructing a knowledge graph of food public opinion in the field of food public opinion, and it is also an important research topic in the field of current information extraction. This paper aims at the multi-entity-to-relationship probl...
Min, C., Xu, J., Xiao, L., Zhao, D., Nie, Y. and Dai, B. (2021). Attentional graph neural network for parking-slot detection.IEEE Robotics and Automation Letters6,2, 3445–3450. ArticleGoogle Scholar Panomruttanarug, B. (2017). Application of iterative learning control in tracking...