with H n being the corresponding centering matrix H n = I n -1 n 11 T . The estimator converges to the population value with 1 √ n . CKA is in the interval [0, 1], where 1 indicates that the representations are strongly dependent while 0 indicates independence. Linear CKA is invariant to isotropic scaling and orthogonal transformation because of the normalization and the inner product kernel, respectively, but not to a general invertible linear transformation. We used the implementation of CKA from.