GitHub

Prometheus Time Series Anomaly Detection with LSTM Autoencoder

This project implements a system for detecting anomalies in time series data collected from Prometheus. It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn ...
IEEE

Anomaly Detection in Complex Systems Using Extended Isolation Forest and Denoising Autoencoder

Abstract: In this paper, we propose an anomaly detection model based on Extended Isolation Forest and Denoising Autoencoder, which achieves unsupervised anomaly detection with good generalization ...
IEEE

MMEVAE: A Time-Varying Rolling Bearing Data Enhancement Method Based on a Multimodal ...

Abstract: Variational autoencoder (VAE) is widely used as a data enhancement technique. However, it faces challenges with inaccurate potential spatial distribution and poor reconstruction quality when ...
Morningstar

Expanding Dyslexia Training: New Free Literacy & Dyslexia Modules on Cox Campus

We are proud to announce the release of the Literacy & Dyslexia modules, now available on Cox Campus, were developed by the Literacy & Dyslexia Team within the University of California | California ...