Hi Frank,
great thank you very much for your answer!
So maybe another question then:
If I have a multivariate linear regression kind of problem of the form:
X @ b = y
with X being a (N x M) matrix, b being a (M x 1) column vector and y being a (N x 1) column vector. And I want to solve this now for X and not for b, what do I do to make this solution numerically tractable. Since my naive solutions would have been:
X = y @ b.t() @ (b @b.t())^-1
but here I obviously have the problem that I have to invert the  projection matrix (b @ b.t())
So is there a common work around for that?
Best regards