In data analysis, GTMs are like a nonlinear version of principal components analysis, which allows high-dimensional data to be modelled as resulting from Gaussian noise added to sources in lower-dimensional latent space.
In generative deformational modelling, the latent and data spaces have the same dimensions, for example, 2D images or 1 audio sound waves.