DeepADoTS
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| DeepADoTS | luminaire | |
|---|---|---|
| 1 | 28 | |
| 538 | 752 | |
| 0.0% | 1.7% | |
| 0.0 | 0.0 | |
| almost 2 years ago | 3 months ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
DeepADoTS
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[D] Anomaly detection without training set?
Other than that, if you're looking for more complicated models you could try and adapt one of the models from this this GitHub repo for your task (this is an open source repo of some SOTA anomaly detection models).
luminaire
What are some alternatives?
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
tods - TODS: An Automated Time-series Outlier Detection System
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
neural_prophet - NeuralProphet: A simple forecasting package
luminol - Anomaly Detection and Correlation library
Informer2020 - The GitHub repository for the paper "Informer" accepted by AAAI 2021.
darts - A python library for user-friendly forecasting and anomaly detection on time series.
pytorch-forecasting - Time series forecasting with PyTorch
Merlion - Merlion: A Machine Learning Framework for Time Series Intelligence
OpenOOD - Benchmarking Generalized Out-of-Distribution Detection
sktime - A unified framework for machine learning with time series