Tag: autoencoder

Triaxial tests and an interpretable machine learning framework show that matrix cementation reverses whether soft rock blocks strengthen or weaken ...

An AI framework combining supervised learning, autoencoder anomaly detection and a multi-agent system detected known and unseen faults in a ...

Most intrusion detection research is tested on artificially balanced datasets, where attack and benign records appear in equal numbers. A ...

Researchers have developed CLeaR, a continual learning framework that lets neural networks handle regression tasks such as wind power forecasting ...

An interpretable brain-age model built on resting-state fMRI from 599 adults links age predictions to specific connectivity circuits, revealing non-linear ...

An unsupervised AI and Earth observation framework screened agricultural water-use anomalies across Cyprus using six hydrological years of data.

A new machine learning framework predicts the mechanical properties of lignin-based polyurethane foams from microscope images within 2.3 percent on ...

Two unsupervised machine-learning methods trained on SuperKEKB beam position monitor data matched each other's detection performance and flagged nine unreported ...

A rank-reduction autoencoder trained on only 421 electromagnetic simulations generated five validated optimized waveguide designs for 6G frequencies that a ...

A new federated framework called FedAE-KMeans trains autoencoders locally on each device and clusters compressed latent representations on a central ...