This is the replication data for our paper "DE-VAE: Revealing Uncertainty in Parametric and Inverse Projections with Variational Autoencoders using Differential Entropy", allowing additional analysis and experiments. The files, per file, below. It includes the experiment data and source code.

For details on the usage, please refer to the README.md in the "source-code.zip" file. All instructions on how to use the method can be found there.

Python, 3.11

PyIP, 25.2

virtualenv, 20.32

The HAR dataset is part of the source code; all other datasets are available via the torchvision library imported by the project. All are well-known datasets for machine learning problems.

Use persistent identifiers from Software Heritage (

) to cite individual files or even lines of the source code.