As a result, classification performance is frequently suboptimal. To address this limitation, we propose leveraging an autoencoder integrated with models pre-trained on diverse HAR datasets to extract ...

A new “periodic table for machine learning,” is reshaping how researchers explore AI, unlocking fresh pathways for discovery.

The Carnegie Foundation for the Advancement of Teaching and the American Council on Education debut a new classification system focused on student success. As widespread public skepticism about the ...

Mount Sinai researchers studying a type of heart disease known as hypertrophic cardiomyopathy (HCM) have calibrated an ...

MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected ...

Artificial intelligence can help urologists and oncologists make treatment recommendations that are objective and evidence-based.

This paper proposes an innovative entropy-aware masked autoencoder framework, namely TMAE, for low-cost traffic flow inference. TMAE leverages a small number of selectively measured regions with few ...

Google’s data classification labels for Gmail are stepping out of the beta spotlight, now available for all. The option means companies get the chance to organize their emails with the help of custom ...

This repository contains a comprehensive implementation of Variational Autoencoders (VAEs) applied to two different image datasets: CIFAR-10 and Fashion-MNIST. The project demonstrates how dataset ...