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Conditional probabilities P(j|i) in high-dimensional space calculated according to a Gaussian distribution centered on each point.

Symmetrized probabilities P(i,j) used to measure mutual similarities between pairs of points in the original space.

Dissimilarity function used to calculate distances in high-dimensional space, typically Euclidean distance but can be adapted.

Variant using a neural network to learn a mapping function from high to low-dimensional space, allowing projection of new data.

Alternative dimensionality reduction algorithm offering better preservation of global structure and faster computation times than t-SNE.

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