Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods”

Last update: Apr 05, 2022

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Deep Learning uncertainity-estimation

Overview

Uncertainty Estimation Methods

Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods”

Reference

If you use this code, please cite the following paper

@inproceedings{liu2021perils,
  title={The Peril of Popular Deep Learning Uncertainty Estimation Methods},
  author={Yehao Liu and Matteo Pagliardini and Tatjana Chavdarova and Sebastian U. Stich},
  booktitle={Bayesian Deep Learning (BDL) Workshop at NeurIPS 2021},
  year={2021}
}

Owner

EPFL Machine Learning and Optimization Laboratory

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Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods”

Related tags

Overview

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Reference

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Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods”

Related tags

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Uncertainty Estimation Methods

Reference

Owner

EPFL Machine Learning and Optimization Laboratory

Solving reinforcement learning tasks which require language and vision

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