1. Böhm, J.N., Berens, P., Kobak, D.: Attraction-repulsion spectrum in neighbor embeddings. J. Mach. Learn. Res. 23(95), 1–32 (2022)
2. Damrich, S., Böhm, J.N., Hamprecht, F.A., Kobak, D.: Contrastive learning unifies $$t$$-SNE and UMAP (2022). https://arxiv.org/abs/2206.01816
3. Dzwinel, W., Wcislo, R., Matwin, S.: 2-D embedding of large and high-dimensional data with minimal memory and computational time requirements. arXiv preprint arXiv:1902.01108 (2019)
4. Dzwinel, W., Wcislo, R., Strzoda, M.: ivga: Visualization of the network of historical events. In: Proceedings of the 1st International Conference on Internet of Things and Machine Learning 2017. ACM (2017)
5. Dzwinel, W., Wcisło, R., Czech, W.: ivga: a fast force-directed method for interactive visualization of complex networks. J. Comput. Sci. 21, 448–459 (2017). ISSN: 1877-7503, https://doi.org/10.1016/j.jocs.2016.09.001, https://www.sciencedirect.com/science/article/abs/pii/S1877750316301430