This repository reproduces results of Anthropic's Sparse Dictionary Learning paper. The codebase is quite rough, but the results are excellent. See the feature interface to browse through the features ...

The methods based on sparse representation and deep learning have shown a great potential for PolSAR image classification. Therefore, a novel PolSAR image classification method based on multilayer ...

While dictionary learning focuses on learning “basis” and “features ... The proposed technique is compared with other deep learning approaches, such as stacked autoencoder, deep belief network, and ...

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While that’s a quick definition of an autoencoder ... of the model will be degraded in comparison to the input data. When designing an autoencoder, machine learning engineers need to pay attention to ...

To solve this problem, we propose a transfer model based on supervised multi-layer dictionary learning (TSMDL) for brain tumor MRI image recognition in this paper. With the help of the knowledge ...

In recent years, deep learning (DL) based methods, such as sparse convolutional denoising autoencoder (SCDA), have been developed for genotype imputation. However, it remains a challenging task to ...

Study: Dictionary learning for integrative, multimodal, and scalable single-cell analysis. Image Credit: Meletios Verras/Shutterstock *Important notice: bioRxiv publishes preliminary scientific ...