Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-uncertainty-deeplearning
This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
https://github.com/ENSTA-U2IS-AI/awesome-uncertainty-deeplearning
- [ICLR2024
- [JMLR2024
- [ICLR2017 - [[TorchUncertainty]](<https://github.com/ENSTA-U2IS-AI/torch-uncertainty>)
- [ICLR2024
- [ICLR2024
- [CVPR2023
- [ICCV2023 - [[PyTorch]](<https://github.com/biggzlar/plausible-uncertainties>)
- [ICML2023 - [[PyTorch]](<https://github.com/danruod/iedl>)
- [ICLR2021 - [[GitHub]](https://github.com/aangelopoulos/conformal_classification)
- [ICML 2023
- [SaTML2023
- [NeurIPS2022
- [AIStats2021
- [ICLR2024
- [ICLR2024
- [CVPR2024 - [[PyTorch]](https://yutingli0606.github.io/SURE/)
- [ICCV2023 - [[PyTorch]](https://github.com/orhir/stg-nf)
- [ICCV2023 - [[PyTorch]](https://github.com/NazirNayal8/RbA)
- [CVPR2023 - [[PyTorch]](https://github.com/txynwpu/Distributional_uncertainty_SOD)
- [ICCV Workshop2023
- [ICCV Workshop2023
- [TPAMI2023 - [[PyTorch]](<https://github.com/Impression2805/FMFP>)
- [TACL2021 - [[PyTorch]](https://github.com/jzbjyb/lm-calibration)
- [Sklearn
- [IEEE Computational Intelligence Magazine
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