meta learningvalidation informationGraphs in real-world applications usually evolve constantly presenting dynamic behaviors such as social networks and transportation networks. Hence, dynamic graph embedding has gained much attention recently. In dynamic graphs, both the topology and node attributes could ...
Subset Node Representation Learning over Large Dynamic Graphs (KDD, 2021) [paper][code] Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space [paper][code] Forecasting Interaction Order on Temporal Graphs (KDD, 2021) Temporal Knowledge Graph Reasoning Based on ...
Graph embedding, aiming to learn low-dimensional representations of nodes while preserving valuable structure information, has played a key role in graph analysis and inference. However, most existing methods deal with static homogeneous topologies, whil
Finally, we propose a scalable and efficient training approach for dynamic GNNs via incremental training and meta-learning. We conduct experiments over eight different dynamic graph datasets on future link prediction tasks. Models built using the ROLAND framework achieve on average 62.7% relative mean ...
Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modeling (SIGKDD, 2024) [paper] SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning (SIGKDD, 2024) [paper][code] Predicting Long-term Dynamics of Complex Networks via Identifying Skeleton ...
标签:Inductive Graph Embedding 概述:针对以往transductive的方式(不能表示unseen nodes)的方法作了改进,提出了一种inductive的方式改进这个问题,该方法学习聚合函数,而不是某个节点的向量 链接:https://papers.nips.cc/paper/6703-inductive-representation-learning-on-large-graphs.pdf 相关数据集: Citation Reddit ...
The learning of node representation vectors involves aggregating multi-dimensional features via GCN to acquire each node embedding vector representation \(\{ H_{T}^{1} ,H_{T}^{2} , \ldots ,H_{T}^{N} \}\), where N signifies the number of nodes. In this study, an improved LSTM ...
Crosscut comes with a selection of prebuilt meta nodes that can be connected via meta lines to manipulate the concrete ink things you draw. Meta nodes make up the low-level programming interface within Crosscut. They have a passing similarity to other node-and-wire programming tools, with ...
24. Continuous-Time Dynamic Graph Learning via Neural Interaction Processes 作者:Xiaofu Chang, et al.(Ant Group) 发表时间:2020 发表于:CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management 标签:CTDG,异质信息,时态点序列过程 概述:针对动态图中并存的拓扑...
标签:Inductive Graph Embedding 概述:针对以往transductive的方式(不能表示unseen nodes)的方法作了改进,提出了一种inductive的方式改进这个问题,该方法学习聚合函数,而不是某个节点的向量表示。 链接:https://papers.nips.cc/paper/6703-inductive-representation-learning-on-large-graphs.pdf 相关数据集: Citation Re...