Nettet6. sep. 2024 · We introduce ``Gated Propagation Network (GPN)'', which learns to propagate messages between prototypes of different classes on the graph, so that learning the prototype of each class benefits from the data of other related classes. In GPN, an attention mechanism is used for the aggregation of messages from …

Learning How to Propagate Messages in Graph Neural Networks

NettetThe meta-learner, called “Gated Propagation Network (GPN)”, learns to propagate messages between prototypes of different classes on the graph, so that learning the prototype of each class benefits from the data of other related classes. In GPN, an attention mechanism aggregates messages from neighboring classes of each class, … Nettetcently, researchers explored using meta-learning to nd op-timal hyper-parameters and appropriately initialize a neural network for few-shot learning [Finn et al., 2024]. 3 Methods In this section, we introduce the proposed MEta Graph Augmentation (MEGA). The architecture of MEGA is de-picted in Figure 2. MEGA proposes to learn informative … harris tweed tote bags

GCL-KGE: Graph Contrastive Learning for Knowledge Graph …

Nettet18. des. 2024 · Meta Propagation Networks for Graph Few-shot Semi-supervised Learning. Kaize Ding, Jianling Wang, James Caverlee, Huan Liu. Inspired by the extensive success of deep learning, graph neural networks (GNNs) have been proposed to learn expressive node representations and demonstrated promising performance in … NettetYet, even with such meta-learning, the low-data problem in the novel classification task still remains. In this paper, we propose Transductive Propagation Network (TPN), a novel meta-learning framework for transductive inference that classifies the entire test set at once to alleviate the low-data problem. NettetMeta-learning extracts common knowledge from learning different tasks and uses it for unseen tasks. It can significantly improve tasks that suffer from insufficient training … harris tweed taransay wool newsboy cap