Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, ...

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the ...

One of the advancements is from data scientist Paril Ghori, who has effectively used an Autoencoder deep learning model to identify anomalies in residential furnaces. Utilizing cutting-edge machine ...

This paper investigates the performance of four machine learning classifiers—Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbours (KNN), and Multi-Layer Perceptron (MLP)—on a cancer ...

These methods belong to the field of machine learning, however there are also many models ... In the following sections, we will apply three different autoencoders which are simple autoencoder, deep ...

Impact Statement: Autoencoder is a popular data-driven modeling technology in deep learning. It can deal with the nonlinear relationships among process variables, and has a powerful feature extraction ...

In the current study, we focus on an autoencoder (AE) as a DL algorithm that allows feature extraction without labels (Hinton, 2006). AE is supervised learning in a deep neural network having an ...