Visual Studio Magazine

Data Dimensionality Reduction Using a Neural Autoencoder with C#

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 ...
ascopubs.org

Evaluating Dimensionality Reduction for Patient-Reported Outcome–Based Survival Modeling in Patients With Head and Neck Cancer

This study aims to improve survival modeling in head and neck cancer (HNC) by integrating patient-reported outcomes (PROs) using dimensionality reduction techniques. PROs capture symptom severity ...
BIOENGINEER

Dual autoencoder framework sharpens single-cell clustering accuracy

A new deep clustering method, scDAEC, combines two autoencoders and multi-head attention to untangle noisy single-cell RNA ...
BetaNews

In praise of the autoencoder

When you consider all the machine learning (ML) algorithms, you’ll find there is a subset of very pragmatic ones: neural networks. They usually require no statistical hypothesis and no specific data ...
techtarget

Autoencoders' example uses augment data for machine learning

Developers frequently turn to autoencoders to organize data for machine learning algorithms to improve the efficiency and accuracy of algorithms with less effort from data scientists. Data scientists ...
techtarget

Autoencoders' example uses augment data for machine learning

Developers frequently turn to autoencoders to organize data for machine learning algorithms to improve the efficiency and accuracy of algorithms with less effort from data scientists. Data scientists ...