Few-shot link prediction in dynamic networks. In WSDM'2022, Paper. Pre-Training Approaches Pre-Training Strategies Contrastive Strategies Deep Graph Contrastive Representation Learning. Preprint, Paper, Code. GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training, In KDD'2020, Paper, Code...
Few-shot Link Prediction in Dynamic Networks In this paper, we propose a novel model based on a meta-learning framework, dubbed as MetaDyGNN, for few-shot link prediction in dynamic networks. Specifically, we propose a meta-learner with hierarchical time interval-wise and node... C Yang,C...
Charting the baby connectome evolution trajectory during the first year after birth plays a vital role in understanding dynamic connectivity development of baby brains. Such analysis requires acquisition of longitudinal connectomic datasets. However, both neonatal and postnatal scans are rarely acquired due...
Deep Neural Networks for Learning Graph Representations论文笔记 Deep Neural Networks for Learning Graph Representations stack anto-encoder 的相关介绍 网络性质 属性、标签 权重 方向 方法 任务 同质 有 有权 有向 matrix factorization node classification 异质 无 无权 无向 random walk link prediction / / ...
In humans, this corresponds to Vygotsky’s concept of a dynamic Zone of Proximal Development (ZPD)81. This is defined to be the difference between a child’s “actual development level as determined by independent problem solving” and “potential development as determined through problem solving ...
Prototypical networks for few-shot learning. In NeurIPS'2017, Paper, Code. Graph Few-shot Learning with Attribute Matching. In CIKM'2020, Paper. Adaptive-Step Graph Meta-Learner for Few-Shot Graph Classification. In CIKM'2020, Paper. Few-shot link prediction in dynamic networks. In WSDM'2022...
(DTAK)13to retain the dynamic structures of behaviour (Fig.4c). To distinguish subtle structures of social behaviour, the temporal points of decomposition for each component are merged through logical addition (Fig.4d). These steps enable the metric of social behaviour, resulting in the ...
3Dynamic Conditional Parameter Prediction Despite the recent success of deep neural networks, it remains challenging to accommodate such models to an extremely large number of categories with limited samples for each, as in the scenario of few-shot learning. Many works to date have mainly focused ...
Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs.Mingyang Chen, Wen Zhang, Wei Zhang, Qiang Chen, Huajun Chen.EMNLP 2019. [pdf] [code] Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection.Shumin Deng, Ningyu Zhang, Jiaojian Kang, ...
The first of these, called reenactment, recreates the abstract process whereby structures are created, following the dynamic of coherence development, starting from simple relational propositions, and combing these to form complex expressions which are in turn integrated to define the comprehensive ...