I have a similarity/distance matrix:
a | b | c a 0 | 1 | 2 b 1 | 0 | 3 c 2 | 3 | 0
I want to build an encoder/model that learns an n-dimensional representation of each of the points in the dataset s.t. the euclidean-difference between the representations produces the difference provided in the matrix, e.g. distance(a,b) = 1 etc.