This was achieved by deriving representational ECG features using a variational autoencoder (VAE) and applying dimensionality reduction via learning a tree (DDRTree) 12 to create a compact, ...

Sustainability Top Articles of 2024, #3: Three Examples of ‘Reduction’ in Healthcare Packaging The #3 most clicked article of 2024: Tekniplex’s Melissa Green spoke at the PACK EXPO Las Vegas ...

AutoencoderZ is an advanced Autoencoder model designed for dimensionality reduction of various data types, such as seismometer and strainmeter data. It features an encoder-decoder architecture that ...

Regular readers know I am a fan of second-look sentencing mechanisms, and I was thus intrigued to see this press report out of Colorado seeming to involve a notable sentence reduction in a notable ...

This project demonstrates the application of a Variational Autoencoder (VAE) for dimensionality reduction, using synthetic "Heartbeat" data as a test case. The analysis includes a comparison between ...

Compared to using PCA for dimensionality reduction, using a neural autoencoder has the big advantage that it works with source data that contains both numeric and categorical data, while PCA works ...

This is called dimensionality reduction. The two most common techniques for dimensionality reduction are using PCA (principal component analysis) and using a neural autoencoder. This article explains ...

Tech New data shows significant reduction in cancer-causing pollution from US refineries: 'An example of a success story of regulations working' "Hopefully … even more industrial facilities will feel ...

For example, a β-variational autoencoder (β-VAE) based on neural networks has been used to encode 3D images of single cells in a low-dimensional latent space with sufficient fidelity to accurately ...