Battle of the dimensionality counter-curses

Evaluating performance of common and uncommon dimensionality reduction tools

UPDATE 5/08/2020: Since we’re on the subject of dimensionality reduction for single-cell data, figured I’d add in the recent dbMAP (diffusion-based Manifold Approximaiton and Projection), yet another dimensionality reduction method for single-cell data, this time based on diffusion maps and UMAP.

UPDATE 6/23/2020: A new technique out of DeepMind: The Geometric Manifold Component Estimator (GeoManCEr). While it’s been optimized for 3D meshes, it seems like this could be big in future research on dimensionality reduction for reinforcement learning (or other tasks related to 3D objects).

Open In Colab

References


Cited as:

@article{mcateer2019dimcc
    title = "Battle of the dimensionality counter-curses",
    author = "McAteer, Matthew",
    journal = "matthewmcateer.me",
    year = "2019",
    url = "https://matthewmcateer.me/blog/dimensionality-counter-curses/"
}

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