537 Open source projects that are alternatives of or similar to singular-spectrum-transformation

Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

Merlion: A Machine Learning Framework for Time Series Intelligence

An open-source, low-code machine learning library in Python

Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

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

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

A repository for code accompanying the manuscript 'An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series' (published at TNNLS)

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Luminaire is a python package that provides ML driven solutions for monitoring time series data.

Tidy anomaly detection

Anomaly detection for streaming time series, featuring automated model selection.

Resources for working with time series and sequence data

An End-to-end Outlier Detection System

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

RNN based Time-series Anomaly detector model implemented in Pytorch.

High-performance time series algorithms for Ruby

A Python toolkit for rule-based/unsupervised anomaly detection in time series

Anomaly detection for temporal data using LSTMs

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

天池“资金流入流出预测——挑战baseline”的解决方案，线上效果143.5

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

[ti]ny [li]ttle machine learning [tool]box - Machine learning, anomaly detection, one-class classification, and structured output prediction

This library was developed for economic analysis in the Brazilian scenario (Investments, micro and macroeconomic indicators)

CNN, RNN, and Bayesian NN classification for ECG time-series (using TensorFlow in Swift and Python)

R Functions implementing UCR Matrix Profile Algorithm

Implementation of feature engineering from Feature engineering strategies for credit card fraud

The Combined Anomalous Object Segmentation (CAOS) Benchmark

Data abstraction, storage, discovery, and serving system

Univariate and multivariate time series forecasting

Model data as beliefs (at a certain time) about events (at a certain time).

Python implementation of AutoPlait (SIGMOD'14) without smoothing algorithm. NOTE: This repository is for my personal use.

Sequence Modeling with Structured State Spaces

Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]

GluonTS Deep Learning with Modeltime

Classifying time series using feature extraction

A time series database prototype with multiple backends

ES6 module of cubism.js, based on d3v5.

Algorithms for causal inference and the detection of dynamical coupling from time series, and for approximation of the transfer operator and invariant measures.

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

TalariaDB is a distributed, highly available, and low latency time-series database for Presto

To process a Sentinel-2 time series with MAJA cloud detection and atmospheric correction processor

midasml package is dedicated to run predictive high-dimensional mixed data sampling models

MemStream: Memory-Based Streaming Anomaly Detection

An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R

A Python Package For System Identification Using NARMAX Models

No description or website provided.

R package for statistical inference using partially observed Markov processes

Hands-on training labs for Deep Learning in Time Series course by CERTIFAI

A Python library for machine-learning and feedback loops on streaming data

API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation

Poor man's time series functionality for PostgreSQL

Mean-Shifted Contrastive Loss for Anomaly Detection

Enables extraction of measurement data from binary files with extension 'raw' used by proprietary software imcFAMOS/imcSTUDIO and facilitates its storage in open source file formats

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

Download and tidy time series data from the Australian Bureau of Statistics in R

Resampling Tools for Time Series Forecasting with Modeltime

Python package for automatically constructing features from multiple time series

PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation (CVPR 2021)