Tensor Network-Constrained Kernel Machines Converge to Gaussian Processes

Tensor Network-constrained kernel machines converge to Gaussian Processes when specifying i.i.d. priors over their parameters. The convergence rate of Tensor Train models is faster than Canonical Polyadic Decomposition models for the same number of parameters.