Incorporating graph information in Bayesian factor analysis with robust and adaptive shrinkage priors.
Sign Up to like & getrecommendations! Published in 2024 at "Biometrics"
DOI: 10.1093/biomtc/ujad014
Abstract: There has been an increasing interest in decomposing high-dimensional multi-omics data into a product of low-rank and sparse matrices for the purpose of dimension reduction and feature engineering. Bayesian factor models achieve such low-dimensional representation… read more here.
Keywords: analysis; bayesian factor; factor; graph information ... See more keywords
Fault Prediction for Electromechanical Equipment Based on Spatial-Temporal Graph Information
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3176891
Abstract: Fault prediction of electromechanical equipment can greatly reduce its maintenance cost and prevent catastrophic damage. In order to realize the accurate fault prediction of electromechanical equipment, a fault prediction method based on spatial-temporal graph information… read more here.
Keywords: information; graph information; fault; spatial temporal ... See more keywords
Graph Information Vanishing Phenomenon in Implicit Graph Neural Networks
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DOI: 10.3390/math12172659
Abstract: Graph neural networks (GNNs) have been highly successful in graph representation learning. The goal of GNNs is to enrich node representations by aggregating information from neighboring nodes. Much work has attempted to improve the quality… read more here.
Keywords: information; gnns; graph neural; graph information ... See more keywords
3D Conformational Generative Models for Biological Structures Using Graph Information-Embedded Relative Coordinates
Sign Up to like & getrecommendations! Published in 2022 at "Molecules"
DOI: 10.3390/molecules28010321
Abstract: Developing molecular generative models for directly generating 3D conformation has recently become a hot research area. Here, an autoencoder based generative model was proposed for molecular conformation generation. A unique feature of our method is… read more here.
Keywords: embedded relative; conformation; graph information; generative models ... See more keywords