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Found 3 papers, 1 papers with code
Decouple Graph Neural Networks: Train Multiple Simple GNNs Simultaneously Instead of One
It extremely limits the application of stochastic optimization algorithms so that the training of GNN is usually time-consuming.
Unsupervised Domain Adaptation Through Transferring both the Source-Knowledge and Target-Relatedness Simultaneously
Unsupervised domain adaptation (UDA) is an emerging research topic in the field of machine learning and pattern recognition, which aims to help the learning of unlabeled target domain by transferring knowledge from the source domain.
A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy
Conclusions: The DeepEM method derived from a deep CNN allows automated particle extraction from raw cryo-EM micrographs in the absence of templates, which demonstrated improved performance, objectivity and accuracy.
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