EurekAlert!

An approach for unsupervised domain adaptation based on integrated autoencoder

Unsupervised domain adaptation has provoked vast amount of attention and research in past decades. Among all the deep-based methods, the autoencoder-based approach have achieved sound performance for ...
Nature

Enhancing mass spectrometry imaging accessibility using convolutional autoencoders for deriving hypoxia-associated peptides from tumors

Spatial omics emerges as a promising tool to characterize intratumoral heterogeneity in solid cancers. For example, mass spectrometry imaging (MSI) allows measuring spatially resolved peptides, ...
Nature

Time-feature attention-based convolutional auto-encoder for flight feature extraction

Civil aviation is constantly striving to improve flight safety. To change the accident-prone nature of Chinese civil aviation and improve flight safety, the Civil Aviation Administration of China ...
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 ...