HDI is a library for the scalable analysis of large and high-dimensional data. It contains scalable manifold-learning algorithms, visualizations and visual-analytics frameworks. HDI is implemented in C++, OpenGL and JavaScript. It is developed within a joint collaboration between the Computer Graphics & Visualization group at the Delft University of Technology and the Division of Image Processing (LKEB) at the Leiden Medical Center.
Authors
- Nicola Pezzotti initiated the HDI project, developed the A-tSNE and HSNE algorithms and implemented most of the visualizations and frameworks.
- Thomas Höllt ported the library to macOS.
Used
HDI is used in the following projects:
- Cytosplore: interactive system for understanding how the immune system works
- Brainscope: web portal for fast, interactive visual exploration of the Allen Atlases of the adult and developing human brain transcriptome
- DeepEyes: progressive analytics system for designing deep neural networks
Reference
Reference to cite when you use HDI in a research paper:
@inproceedings{Pezzotti2016HSNE,
title={Hierarchical stochastic neighbor embedding},
author={Pezzotti, Nicola and H{\"o}llt, Thomas and Lelieveldt, Boudewijn PF and Eisemann, Elmar and Vilanova, Anna},
journal={Computer Graphics Forum},
volume={35},
number={3},
pages={21--30},
year={2016}
}
@article{Pezzotti2017AtSNE,
title={Approximated and user steerable tsne for progressive visual analytics},
author={Pezzotti, Nicola and Lelieveldt, Boudewijn PF and van der Maaten, Laurens and H{\"o}llt, Thomas and Eisemann, Elmar and Vilanova, Anna},
journal={IEEE transactions on visualization and computer graphics},
volume={23},
number={7},
pages={1739--1752},
year={2017}
}
Building
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Tutorial
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