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Multi-facet clustering variational autoencoders. Adv. Neural Inf. Process. Syst. 34, 8676–8690 (2021). Google Scholar Fortuin, V., Hüser, M., Locatello, F., Strathmann, H. & Rätsch, G. SOM-VAE: interpretable discrete representation learning on time series. In International ...
consolidation: a partial input is mapped to latent variables whose return projections to the sensory neocortex via HF then decode these back into a sensory experience.f, Imagination: latent variables are decoded into an experience via HF and return projections to the neocortex.g, Semantic memory: ...
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However, the complexity and high dimensionality of the data features may lead to overlapping and ambiguous subtypes during clustering. Results In this study, we propose GDEC, a multi-task generative deep neural network designed for precise digestive tract cancer subtyping. The network optimization ...
(Fig.2c). When we trained siVAE and provided batch information during training, clustering by batch is eliminated while the clustering by cell type is still preserved (Fig.2d). These results suggest that siVAE is a viable alternative to existing dimensionality reduction approaches that can be ...
0.85 (P=2.531×10−13) between the original and cross-generated datasets.f,gResults when the model was trained on independent reference multi-omics datasets: (f) UMAP visualization illustrates the clustering resemblance between the original and cross-generated matched mouse scRNA-seq data.gCell ...
The researchers used AI to examine its impact on supply chain risk management, providing a unique perspective rooted in the resource-based view. They employed a multi-faceted approach that included partial least squares-based structural equation modelling and artificial neural network, showcasing AI's...
Ran, A. et al. Fast clustering of retired lithium-ion batteries for secondary life with a two-step learning method.ACS Energy Lett.7, 3817–3825 (2022). ArticleCASGoogle Scholar Lai, X. et al. Rapid sorting and regrouping of retired lithium-ion battery modules for echelon utilization based...
aThe structure of the initial dataset D0. The 2D PCA plots of the initial dataset D0subdivided by (b) the K-Means clustering algorithm and (c) the data clustering based on the number of constituent elements in the alloy data.dTheF-measure of the trained ANN models based on different data...