The nptsne package is designed to export a number of python classes that wrap GPGPU linear complexity tSNE or the hierarchical SNE (hSNE) method.
When using nptsne please include the following citations when using t-SNE and or using HSNE:
using t-SNE
*Pezzotti, N., Thijssen, J., Mordvintsev, A., Höllt, T., Van Lew, B., Lelieveldt, B.P.F., Eisemann, E., Vilanova, A., (2020), "GPGPU Linear Complexity t-SNE Optimization" in IEEE Transactions on Visualization and Computer Graphics.
doi: 10.1109/TVCG.2019.2934307
keywords: {Minimization;Linear programming;Computational modeling;Approximation algorithms;Complexity theory;Optimization;Data visualization;High Dimensional Data;Dimensionality Reduction;Progressive Visual Analytics;Approximate Computation;GPGPU},
URL: https://doi.org/10.1109/TVCG.2019.2934307 *
using HNSE
*Pezzotti, N., Höllt, T., Lelieveldt, B., Eisemann, E., Vilanova, A., (2016), "Hierarchical Stochastic Neighbor Embedding" in Computer Graphics Forum, 35: 21-30.
doi:10.1111/cgf.12878
keywords: {Categories and Subject Descriptors (according to ACM CCS), I.3.0 Computer Graphics: General},
URL: https://doi.org/10.1111/cgf.12878 *
The t-SNE and HSNE implementations are the original work of the authors named in the literature.
Full documentation is available at the nptsne doc pages