Suggested further readings

Principal component analysis (PCA):

Shlens (2014) A tutorial on principal component analysis. arXiv https://arxiv.org/abs/1404.1100

Other linear dimensionality reductions:

Hyvarinen & Oja (2000) Independent component analysis: algorithms and applications. https://www.sciencedirect.com/science/article/abs/pii/S0893608000000265

Gillis (2014) The why and how of nonnegative matrix factorization. https://arxiv.org/abs/1401.5226

Nonlinear dimensionality reduction:

Wattenberg et al. (2016) How to Use t-SNE Effectively Distill. http://doi.org/10.23915/distill.00002

Understanding UMAP. https://pair-code.github.io/understanding-umap/

Dimensionality reduction in systems neuroscience:

Cunningham & Yu (2014) Dimensionality reduction for large-scale neural recordings. Nature Neuroscience https://www.nature.com/articles/nn.3776

Brain-computer interface work shown in Outro:

Golub et al. (2016) Brain–computer interfaces for dissecting cognitive processes underlying sensorimotor control. Current Opinion in Neurobiology https://www.sciencedirect.com/science/article/abs/pii/S095943881500183X

Sadtler et al. (2014) Neural constraints on learning. Nature https://www.nature.com/articles/nature13665

Golub et al. (2018) Learning by neural reassociation. Nature Neuroscience https://www.nature.com/articles/s41593-018-0095-3