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https://www.mdpi.com/1424-8220/22/7/2648 Word Embedding Distribution Propagation Graph Network for Few-Shot Learning Few-shot learning (FSL) is of great significance to the field of machine learning. The ability to learn and generalize using a small number of samples is an... word embedding propagation graph few shot distribution network https://arxiv.org/abs/2010.12408v2 [2010.12408v2] On the Equivalence of Decoupled Graph Convolution Network and Label Propagation Abstract page for arXiv paper 2010.12408v2: On the Equivalence of Decoupled Graph Convolution Network and Label Propagation https://deepai.org/publication/g-signatures-global-graph-propagation-with-randomized-signatures G-Signatures: Global Graph Propagation With Randomized Signatures | DeepAI Feb 17, 2023 - 02/17/23 - Graph neural networks (GNNs) have evolved into one of the most popular deep learning architectures. However, GNNs suffer from over... g randomized deepai https://openreview.net/forum?id=F3kUFcNRWJ Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs | OpenReview Graph neural networks (GNNs) are widely used for learning node embeddings in graphs, typically adopting a message-passing scheme. This approach, however, leads... at scale graph learning https://aclanthology.org/2024.findings-emnlp.257/ Graph-tree Fusion Model with Bidirectional Information Propagation for Long Document Classification... Sudipta Singha Roy, Xindi Wang, Robert Mercer, Frank Rudzicz. Findings of the Association for Computational Linguistics: EMNLP 2024. 2024.