20 citations · 27 across the 4 of their papers we have counts for
4 papers
Accelerating hyperbolic t-SNE
Martin Skrodzki, Hunter van Geffen, Nicolas F. Chaves-de-Plaza +3
The need to understand the structure of hierarchical or high-dimensional data is present in a variety of fields. Hyperbolic spaces have proven to be an important tool for embedding…
Navigating Perplexity: A linear relationship with the data set size in t-SNE embeddings
Martin Skrodzki, Nicolas F. Chaves-de-Plaza, Thomas Höllt +2
Widely used pipelines for analyzing high-dimensional data utilize two-dimensional visualizations. These are created, for instance, via t-distributed stochastic neighbor embedding (…
Incorporating Texture Information into Dimensionality Reduction for High-Dimensional Images
Alexander Vieth, Anna Vilanova, Boudewijn Lelieveldt +2
High-dimensional imaging is becoming increasingly relevant in many fields from astronomy and cultural heritage to systems biology. Visual exploration of such high-dimensional data…
Visual cohort comparison for spatial single-cell omics-data
Antonios Somarakis, Marieke E. Ijsselsteijn, Sietse J. Luk +4
Spatially-resolved omics-data enable researchers to precisely distinguish cell types in tissue and explore their spatial interactions, enabling deep understanding of tissue functio…