Image anomaly detection has emerged as a crucial field in data analysis, pivotal in identifying unusual patterns in vast visualizations, with implications across numerous industries and academic ...

Compared with the Variational Autoencoder(VAE), a generative model that can be used to model prior data distribution, IWAE has a strictly tighter variational lower bound derive from different weighted ...

Autoencoder basics Autoencoders are based on neural networks, and the network consists of two parts: an encoder and a decoder. Encoder compresses the N-dimensional input (e.g. a frame of sensor data) ...

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 ...