ivis: dimensionality reduction in very large datasets using Siamese Networks

R Python Submitted 18 July 2019Published 06 August 2019
Review

Editor: @lpantano (all papers)
Reviewers: @SaskiaFreytag (all reviews), @kevinrue (all reviews)

Authors

Benjamin Szubert, Ignat Drozdov (0000-0001-6727-4688)

Citation

Szubert et al., (2019). ivis: dimensionality reduction in very large datasets using Siamese Networks. Journal of Open Source Software, 4(40), 1596, https://doi.org/10.21105/joss.01596

@article{Szubert2019, doi = {10.21105/joss.01596}, url = {https://doi.org/10.21105/joss.01596}, year = {2019}, publisher = {The Open Journal}, volume = {4}, number = {40}, pages = {1596}, author = {Benjamin Szubert and Ignat Drozdov}, title = {ivis: dimensionality reduction in very large datasets using Siamese Networks}, journal = {Journal of Open Source Software} }
Copy citation string · Copy BibTeX  
Tags

dimensionality reduction unsupervised learning neural network

Altmetrics
Markdown badge

 

License

Authors of JOSS papers retain copyright.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

Public user content licensed CC BY 4.0 unless otherwise specified.
ISSN 2475-9066