Symmetric matrices of huge size with many zero entries, called sparse symmetric matrices, are nowadays studied actively in the context of artificial intelligence and data science. One of the efficient ...

This article gives a formal definition of a lognormal family of probability distributions on the set of symmetric positive definite (SPD) matrices, seen as a matrix-variate extension of the univariate ...

Positive definite matrices play a central role in mathematics, physics, statistics and engineering due to their unique properties and widespread applicability. These matrices, which are characterised ...

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This is a preview. Log in through your library . Abstract Let X:p × n be a matrix of random real variates such that the column vectors of X are independently and identically distributed as ...

Abstract: The advent of unmanned aerial vehicles (UAVs) has initiated a revolutionary era in human action recognition, profoundly influencing various domains. This transition underscores the critical ...

Ablation,Action Recognition,Advances In This Area,Barycenter,Batch Normalization,Convolutional Neural Network,Covariance Matrix,Deep Neural Network,Diffeomorphism ...