ENSTA-U2IS-AI/awesome-uncertainty-deeplearning
A curated collection of papers, code, and resources on uncertainty estimation in deep learning models.
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This repository aggregates surveys, theoretical works, and implementations covering Bayesian methods, ensemble approaches, conformal predictions, calibration techniques, and out-of-distribution detection in deep neural networks. It organizes resources across topics like epistemic vs aleatoric uncertainty, selective classification, and anomaly detection. The collection serves as a reference for researchers and practitioners working on uncertainty quantification in machine learning systems.
Frequently asked
- What is ENSTA-U2IS-AI/awesome-uncertainty-deeplearning?
- A curated collection of papers, code, and resources on uncertainty estimation in deep learning models.
- Is awesome-uncertainty-deeplearning open source?
- Yes — ENSTA-U2IS-AI/awesome-uncertainty-deeplearning is open source, released under the MIT license.
- How popular is awesome-uncertainty-deeplearning?
- ENSTA-U2IS-AI/awesome-uncertainty-deeplearning has 816 stars on GitHub.
- Where can I find awesome-uncertainty-deeplearning?
- ENSTA-U2IS-AI/awesome-uncertainty-deeplearning is on GitHub at https://github.com/ENSTA-U2IS-AI/awesome-uncertainty-deeplearning.