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Dimensionality Reduction
Dimensionality Reduction methods transform data from a high-dimensional space into a low-dimensional space so that the low-dimensional space retains the most important properties of the original data. Below you can find a continuously updating list of dimensionality reduction methods.
Methods
All 8 methods in this collection, most-tagged first. Year is the archive's introduced_year; the archive stores 2000 when it has none, shown here as “–”. Papers counts distinct papers the archive tags with the method. Click a heading to sort.
| PCA Principal Components Analysis | – | 1,323 |
| Variational Inference | – | 846 |
| LDA Linear Discriminant Analysis | – | 459 |
| Latent Diffusion Model | – | 366 |
| AE Autoencoders | – | 292 |
| ICA Independent Component Analysis | – | 261 |
| Parametric UMAP | – | 4 |
| POLCANET Principal Orthogonal Latent Components Analysis Network | – | 1 |