Hi,
Thanks for great research. However, it seems that covariance loss is implemented different from the description in your paper.
(https://github.com/changun/CollMetric/blob/master/CML.py#L174) According to your paper, covariance loss is defined as 1/N(||C||_f - ||diag(C)||_2^2), where C is a covariance matrix between all pairs of dimensions. But you implemented it as summation of off-diagonal elements of covariance matrix, which may result in negative scale. Could you provide some more explanation about covariance loss?
Hi,
Thanks for great research. However, it seems that covariance loss is implemented different from the description in your paper.
(https://github.com/changun/CollMetric/blob/master/CML.py#L174) According to your paper, covariance loss is defined as 1/N(||C||_f - ||diag(C)||_2^2), where C is a covariance matrix between all pairs of dimensions. But you implemented it as summation of off-diagonal elements of covariance matrix, which may result in negative scale. Could you provide some more explanation about covariance loss?