Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...

The denomination had ordered agencies to determine the “appropriateness” of the book for Christians. The Presbyterian Church in America’s bookstore wouldn’t recommend or sell Jesus Calling, but the ...

1 School of Technology, Computer Science & I.T Department, Njala University, Bo, Sierra Leone. 2 School of Electrical Engineering, Xi’an Jiaotong University, Xi’an, China. 3 School of Software ...

Sparse autoencoders are central tools in analyzing how large language models function internally. Translating complex internal states into interpretable components allows researchers to break down ...

Abstract: The accurate monitoring of abnormal production conditions in cement process is the basis of intelligent control, which is of great significance to improve the intelligent level of cement ...

This study aims to explore an autoencoder-based method for generating brain MRI images of patients with Autism Spectrum Disorder (ASD) and non-ASD individuals, and to discriminate ASD based on the ...

An artificial intelligence (AI)-assisted hardware design platform enables engineers to find the right components for their design projects using machine learning and smart algorithms. It selects the ...

Variational Autoencoder for Dimensionality Reduction on Synthetic Heartbeat Data This project demonstrates the application of a Variational Autoencoder (VAE) for dimensionality reduction, using ...