aweSOM: a CPU/GPU-accelerated Self-organizing Map and Statistically Combined Ensemble Framework for Machine-learning Clustering Analysis
Ha et al., (2025). aweSOM: a CPU/GPU-accelerated Self-organizing Map and Statistically Combined Ensemble Framework for Machine-learning Clustering Analysis. Journal of Open Source Software, 10(108), 7613, https://doi.org/10.21105/joss.07613
Authors
- Joonas Nättilä (ORCID: https://orcid.org/0000-0002-3226-4575)
- Jordy Davelaar (ORCID: https://orcid.org/0000-0002-2685-2434)
- Trung Ha (ORCID: https://orcid.org/0000-0001-6600-2517)
Institutions
- University of North Texas (US)
- Albert Einstein College of Medicine (US)
- University of Helsinki (FI)
- Princeton University (US)
- University of Massachusetts Amherst (US)
- Helsinki Institute of Physics (FI)
- Flatiron Health (United States) (US)
- Flatiron Institute (US)
- Columbia University (US)
Publication Details
- Journal
- The Journal of Open Source Software
- Published
- 2025-04-04
- DOI
- https://doi.org/10.21105/joss.07613
- Citations
- 1
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- National Aeronautics and Space Administration
- Space Telescope Science Institute
- Flatiron Health