E cient unbiased data analysis is a major challenge for laboratories handling large ow and
mass cytometry datasets. We present EmbedSOM, a non-linear embedding algorithm based …

Interactive visual exploration of large and multidimensional data still needs more efficient
ND → 2D data embedding (DE) algorithms. We claim that the visualization of very high …

We investigate how the quality and computational complexity of the golden standards of
high-dimensional data (HDD) visualisation-the t-SNE and UMAP algorithms-change with …

The main flaw of neural network ensembling is that it is exceptionally demanding
computationally, especially, if the individual sub-models are large neural networks, which …

Interactive visual exploration of large high-dimensional data (HDD) plays a very important
role in various scientific fields that require aggregated information about the …

Efficient unbiased data analysis is a major challenge for laboratories handling large
cytometry datasets. We present EmbedSOM, a non-linear embedding algorithm based on …

We investigate how the quality and computational complexity of the golden standards of
high-dimensional data (HDD) visualisation-the t-SNE and UMAP algorithms-change with …

Embedding of high-dimensional data to 2D (3D) Euclidean space is an important data
science technique for visual exploration of data and knowledge extraction. Though many …