lapalap/dora
GitHub repository for DORA: Data-agnOstic Representation Analysis paper. DORA allows to find outlier representations in Deep Neural Networks.
This tool helps machine learning engineers and researchers analyze Deep Neural Networks for unintended learning. It takes your pre-trained neural network as input and outputs identified 'infected' neurons or representations that might be learning spurious, irrelevant concepts. The user is a machine learning practitioner who wants to ensure their models are robust and reliable.
No commits in the last 6 months.
Use this if you need to automatically detect and understand anomalous behaviors or 'infected' components within your deep learning models.
Not ideal if you are looking for a tool to explain overall model predictions to a non-technical audience or to interpret why a specific input led to a specific output.
Stars
27
Forks
3
Language
Python
License
MIT
Category
Last pushed
Mar 19, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/lapalap/dora"
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.