ashafaei/out-of-distribution-detection
The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks
This is a reference for machine learning practitioners and researchers working with deep neural networks. It helps you understand and compare various techniques for detecting when your model encounters data it wasn't trained on. It takes in research papers and open-source implementations, and provides insights into their computational costs, memory needs, and overall effectiveness.
118 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher developing robust deep learning models and need to ensure your models don't make unreliable predictions on unfamiliar data.
Not ideal if you are looking for a plug-and-play software library for immediate integration into an existing application without diving into research.
Stars
118
Forks
5
Language
—
License
MIT
Category
Last pushed
Dec 31, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ashafaei/out-of-distribution-detection"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
yzhao062/pyod
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
unit8co/darts
A python library for user-friendly forecasting and anomaly detection on time series.
elki-project/elki
ELKI Data Mining Toolkit
raphaelvallat/antropy
AntroPy: entropy and complexity of (EEG) time-series in Python
Minqi824/ADBench
Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.