Disclaimer: This is reaching the limits of my math abilities.
The differences comes in the fact that higher dimensional tuples may contain data that is independent of other fields. Say, if you have a tuple that's: (name, dob, address,) and you have a projection function that accepts such a 3-tuple and returns a 2-tuple of (name, dob,). For that function, the address dimension has no relationship at all to the other fields, meaning, that there is not unproject function that a person could create such that 3_tuple == unproject(project(3_tuple)).
With manifolds, the higher dimensions can have a relationship with lower dimensional data, and such a relationship can be encoded into a function. What the research appear to have designed is a system that, given a priori knowledge of task and enough n-tuples for learning, can produce and approximation of such an unproject function.
Thus, after learning, they have a system where, unproject(project(n_tuple)) ~= n+1_tuple. Because they were able to inform the learning system about the nature of the relationship between the two dimensions.
The differences comes in the fact that higher dimensional tuples may contain data that is independent of other fields. Say, if you have a tuple that's: (name, dob, address,) and you have a projection function that accepts such a 3-tuple and returns a 2-tuple of (name, dob,). For that function, the address dimension has no relationship at all to the other fields, meaning, that there is not unproject function that a person could create such that 3_tuple == unproject(project(3_tuple)).
With manifolds, the higher dimensions can have a relationship with lower dimensional data, and such a relationship can be encoded into a function. What the research appear to have designed is a system that, given a priori knowledge of task and enough n-tuples for learning, can produce and approximation of such an unproject function.
Thus, after learning, they have a system where, unproject(project(n_tuple)) ~= n+1_tuple. Because they were able to inform the learning system about the nature of the relationship between the two dimensions.