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 ...

Actress Priscilla Pointer, who starred on Dallas for several seasons in the 1980s, has died, and her on-screen daughter, Victoria Principal, turned to social media to tribute her television mom.

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 ...

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 ...

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

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation of a dataset that has fewer columns. Imagine that you have a dataset that has many ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique that transforms a dataset into one with fewer columns, useful for creating a graph of ...