In the task of multi-label classification, it is a key challenge to determine the correlation between labels. One solution to this is the Target Embedding Autoencoder (TEA), but most TEA-based ...

This project examined whether a deep autoencoder embedding could improve clustering of bulk RNA-seq data from green anole # muscle stem cells (MuSCs) relative to standard methods. Using features of ...

In the task of multi-label classification, it is a key challenge to determine the correlation between labels. One solution to this is the Target Embedding Autoencoder (TEA), but most TEA-based ...