NettetThe objective of the graph augmenter is to promote our feature extraction network to learn a more discriminative feature representation, which motivates us to propose a meta-learning paradigm. Empirically, the experiments across multiple benchmark datasets demonstrate that MEGA outperforms the state-of-the-art methods in graph self … Nettet11. sep. 2024 · The meta-learner, called "Gated Propagation Network (GPN)", learns to propagate messages between prototypes of different classes on the graph, so that …
Learning to Propagate for Graph Meta-Learning
Nettet15. apr. 2024 · 3.1 Overview. In this section, we describe our model which utilizes contrastive learning to learn the KG embedding. We present an encoder-decoder … NettetMeta-sgd: Learning to learn quickly for few-shot learning. arXiv preprint arXiv:1707.09835 (2024). Google Scholar; Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, and Chengqi Zhang. 2024. Learning to propagate for graph meta-learning. In NeurIPS. Google Scholar; Xiao Liu, Fanjin Zhang, Zhenyu Hou, ZhaoyuWang, Li Mian, Jing … honey oak kitchen table and chairs
[2304.03093] Inductive Graph Unlearning
Nettet15. apr. 2024 · 3.1 Overview. In this section, we describe our model which utilizes contrastive learning to learn the KG embedding. We present an encoder-decoder model called GCL-KGE in Fig. 1.The encoder learns knowledge graph embedding through the graph attention network to aggregate neighbor’s information. NettetLearning to Propagate for Graph Meta-Learning . Meta-learning extracts common knowledge from learning different tasks and uses it for unseen tasks. It can significantly improve tasks that suffer from insufficient training data, e.g., few shot learning. In most meta-learning methods, tasks are implicitly related by sharing parameters or optimizer. 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 … honey oak kitchen pantry cabinet