MemStream: Memory-Based Streaming Anomaly Detection

Memory-augmented Deep Autoencoder (https://arxiv.org/abs/1904.02639) for Vector Data

MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.

About Code release for "Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy" (ICLR 2022 Spotlight), https://openreview.net/forum?id=LzQQ89U1qm_

A Library for Advanced Deep Time Series Models.

This is the official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting".

Multivariate Time Series Transformer, public version

Task-Aware Reconstruction for Time-Series Transformer

The Numenta Anomaly Benchmark

Official code for "Memory-Augmented U-Transformer for Multivariate Time Series Anomaly Detection" Code will come soon!

List of tools & datasets for anomaly detection on time-series data.

An official implementation of "Learning Memory-guided Normality for Anomaly Detection" (CVPR 2020) in PyTorch.