Abstract: This paper addresses the problem of detecting multidimensional subspace signals in noise of unknown covariance. It is assumed that a primary channel of measurements, possibly consisting of ...
Abstract: Disentanglement learning aims to separate explanatory factors of variation so that different attributes of the data can be well characterized and isolated, which promotes efficient inference ...