Can we assume latent vectors are Euclidean? I want to understand the mathematical nature of latent vectors, which I am pointing to general latent vectors which we can sample from an intermediate layer from a neural network.
Can we assume they are Euclidean?
Can we apply Euclidean geometry (e.g. distance/ area/ volume calculations) on latent vectors?

They're n-dimensional vectors. Associating them with an Euclidean or non-Euclidean space/geometric rules will only be based on your assumptions. Therefore, yes.
