ENSTA-U2IS-AI/awesome-uncertainty-deeplearning
This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
This is a curated collection of resources that helps machine learning practitioners understand and implement methods for estimating how certain their deep learning models are about their predictions. It provides a comprehensive list of papers, code examples, datasets, and surveys on uncertainty quantification techniques. Data scientists and AI researchers can use this to research the field of uncertainty in deep learning, to choose appropriate techniques, and to apply them to their models.
787 stars.
Use this if you need to build more trustworthy and reliable AI systems by understanding the confidence of your model's predictions.
Not ideal if you are looking for a pre-packaged software solution to integrate directly into an existing application without needing to understand the underlying methods.
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787
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MIT
Last pushed
Dec 05, 2025
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