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Identification of Anomalous Diffusion Sources by Unsupervised Learning
Fractional Brownian motion (fBm) is a ubiquitous diffusion process in which the memory effects of the stochastic transport result in the mean squared particle displacement following a power law, $\langle {\Delta r}^2 \rangle \sim t^{\alpha}$, where the diffusion exponent $\alpha$ characterizes whether the transport is subdiffusive, ($\alpha<1$), diffusive ($\alpha = 1$), or superdiffusive, ($\alpha >1$).
Distributed Non-Negative Tensor Train Decomposition
Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors.
A Neural Network for Determination of Latent Dimensionality in Nonnegative Matrix Factorization
An important input for NMF is the latent dimensionality of the data, that is, the number of hidden features, K, present in the explored data set.
