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Visualizing High-Dimensional Temporal Data Using Direction-Aware t-SNE
Most existing dimensionality reduction techniques, such as t-SNE and UMAP, do not take into account the temporal or relational nature of the data when constructing the embeddings, resulting in temporally cluttered visualizations that obscure potentially interesting patterns.
Explainable Point-Based Document Visualizations
Popular techniques to construct data maps are t-SNE and UMAP.
Data Fusion by Matrix Factorization
For most problems in science and engineering we can obtain data sets that describe the observed system from various perspectives and record the behavior of its individual components.
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