Data underlying the publication: Robust Multi-Modal Density Estimation

doi:10.4121/61f283ae-c30c-42d1-9a7c-89b454e013b3.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/61f283ae-c30c-42d1-9a7c-89b454e013b3
Datacite citation style:
Mészáros, Anna; Julian Schumann (2024): Data underlying the publication: Robust Multi-Modal Density Estimation. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/61f283ae-c30c-42d1-9a7c-89b454e013b3.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This dataset contains three folders related to the samples used for validating the approach proposed in "ROME: Robust Multi-Modal Density Estimation". The folder "Fitted Distributions" contains the distributions obtained by using both ROME and other methods which we compare to in the publication. "Log Likelihoods" contains the likelihood values for the samples that make up the previously mentioned distributions. Lastly, "Results" contain the metric values which provide the basis for the final data analysis and results reported in the publication.


This data is to be used in conjunction to the code available at https://github.com/anna-meszaros/ROME/tree/main , and contains the results obtained using this code.

history
  • 2024-02-14 first online, published, posted
publisher
4TU.ResearchData
format
zip files containing binary (Python pickle) files
associated peer-reviewed publication
Robust Multi-Modal Density Estimation
funding
  • NWO-NWA “Acting under uncertainty” (ACT) (grant code NWA.1292.19.298.) NWO
organizations
TU Delft, Faculty of Mechanical Engineering, Department of Cognitive Robotics

DATA

files (4)