Results 11 to 20 of about 748,129 (177)
Node Classification in Uncertain Graphs [PDF]
Proceedings of the 26th International Conference on Scientific and Statistical Database Management, 2014 In many real applications that use and analyze networked data, the links in the network graph may be erroneous, or derived from probabilistic techniques.
Aggarwal, Charu +2 more
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Mixup for Node and Graph Classification [PDF]
Proceedings of the Web Conference 2021, 2021 Mixup is an advanced data augmentation method for training neural network based image classifiers, which interpolates both features and labels of a pair of images to produce synthetic samples. However, devising the Mixup methods for graph learning is challenging due to the irregularity and connectivity of graph data. In this paper, we propose the Mixup
Yiwei Wang 0001 +4 more
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Bayesian Node Classification for Noisy Graphs [PDF]
2021 IEEE Statistical Signal Processing Workshop (SSP), 2021 Graph neural networks (GNN) have been recognized as powerful tools for learning representations in graph structured data. The key idea is to propagate and aggregate information along edges of the given graph. However, little work has been done to analyze the effect of noise on their performance.
Hakim Hafidi +3 more
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Uncertainty Propagation in Node Classification
2022 IEEE International Conference on Data Mining (ICDM), 2022 Quantifying predictive uncertainty of neural networks has recently attracted increasing attention. In this work, we focus on measuring uncertainty of graph neural networks (GNNs) for the task of node classification. Most existing GNNs model message passing among nodes. The messages are often deterministic.
Xu, Zhao +3 more
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GATSMOTE: Improving Imbalanced Node Classification on Graphs via Attention and Homophily
Mathematics, 2022 In recent decades, non-invasive neuroimaging techniques and graph theories have enabled a better understanding of the structural patterns of the human brain at a macroscopic level.
Yongxu Liu, Zhi Zhang, Yan Liu, Yao Zhu
doaj +1 more source
Virtual Node Tuning for Few-shot Node Classification
CoRR, 2023 Accepted to KDD ...
Zhen Tan 0001 +3 more
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Node Classification Algorithm Based on Information Propagation Node Set for CTDN [PDF]
Jisuanji gongcheng, 2021 The study described in this paper addresses the problem of node classification in Continuous-Time Dynamic Network(CTDN).In this work, an information propagation node set is defined according to the features of the actual network information propagation ...
HUANG Xin, LI Yun, XIONG Jinyu
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One Node at a Time: Node-Level Network Classification
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), 2021 8 pages, 5 ...
Saray Shai, Isaac Jacobs, Peter J. Mucha
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Applied Sciences, 2023 In recent years, graph neural networks (GNNs) have achieved great success in handling node classification tasks. However, as data explosively grows in various industries, the problem of class imbalance becomes increasingly severe.
Liying Zhang, Haihang Sun
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CE-Net: A Coordinate Embedding Network for Mismatching Removal
IEEE Access, 2021 Mismatching removal is at the core yet still a challenging problem in the photogrammetry and computer vision field. In this paper, we propose a coordinate embedding network (named CE-Net).
Shiyu Chen +5 more
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