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  • Jörg Martin's avatar
    c07920e2
    NonEiV training included · c07920e2
    Jörg Martin authored 
    This covers all regression datasets treated in the MC Dropout and Deep
Ensemble paper. Results are comparable or even better. For multivariate
dataset, the decouple_dimensions keyword in the evaluation scripts can
be used to follow the (rather weird) convention of these papers.
    c07920e2
    History
    NonEiV training included
    Jörg Martin authored 
    This covers all regression datasets treated in the MC Dropout and Deep
Ensemble paper. Results are comparable or even better. For multivariate
dataset, the decouple_dimensions keyword in the evaluation scripts can
be used to follow the (rather weird) convention of these papers.
README.md 3.19 KiB

Errors-in-Variables for deep learning: rethinking aleatoric uncertainty - supplementary material

This directory lists the source code for the article Errors-in-Variables for deep learning: rethinking aleatoric uncertainty.

Requirements

The software used to produce the results from the preprint was written in Python 3. If not already installed, the easiest way to set up Python is usually via Anaconda. To use the software, the installation of some additional packages is required. This is discussed below. To avoid any global impacts on the Python install, especially if the system interpreter is used, it might be preferable to do the following in a virtual environment, either in Anaconda or by using the venv module. The Python version used for the results in the preprint is 3.9.7.

Installing additional packages (except PyTorch)

The Python packages to use this software, except for PyTorch which we will discuss below, can be installed by using the file requirements.txt

pip install -r requirements.txt

When using Anaconda, make sure that python is installed in the virtual environment. If not, use conda install python or conda install python=3.9.7 before running the pip command.

When running into version issues:

There is an according requirements_without_versions.txt file that does not insist on the versions from the preprint. In case of a version conflict, e.g. with pre-installed packages, this file can be used instead. When still running into problems, the packages listed in requirements_without_versions.txt should be installed one after the other.