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Found 3 papers, 1 papers with code
MultiHead MultiModal Deep Interest Recommendation Network
How to obtain the information that users are interested in from the large amount of information has become an issue of great concern to users and even business managers.
RRLFSOR: An Efficient Self-Supervised Learning Strategy of Graph Convolutional Networks
Graph Convolutional Networks (GCNs) are widely used in many applications yet still need large amounts of labelled data for training.
Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning
In this study, we propose a deep neural network based few-shot learning approach for rolling bearing fault diagnosis with limited data.
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