aamini/evidential-deep-learning
Learn fast, scalable, and calibrated measures of uncertainty using neural networks!
This project helps machine learning engineers build more reliable AI models. It takes a standard neural network and modifies its final layers to output not just a prediction, but also a quantifiable measure of confidence in that prediction. This allows developers to understand when their models are uncertain, even on new or unusual data, making AI systems safer and more trustworthy.
513 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are developing AI models where understanding the model's confidence in its predictions is critical for safety or decision-making.
Not ideal if you are a business user or practitioner simply looking for a ready-to-use AI solution, as this requires direct modification of neural network architectures.
Stars
513
Forks
101
Language
Python
License
Apache-2.0
Last pushed
Aug 31, 2021
Commits (30d)
0
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