  Recently, codes in the sum-rank metric attracted attention due to several
applications in e.g. multishot network coding, distributed storage and
quantum-resistant cryptography. The sum-rank analogs of Reed-Solomon and
Gabidulin codes are linearized Reed-Solomon codes. We show how to construct
$h$-folded linearized Reed-Solomon (FLRS) codes and derive an
interpolation-based decoding scheme that is capable of correcting sum-rank
errors beyond the unique decoding radius. The presented decoder can be used for
either list or probabilistic unique decoding and requires at most
$\mathcal{O}(sn^2)$ operations in $\mathbb{F}_{q^m}$, where $s \leq h$ is an
interpolation parameter and $n$ denotes the length of the unfolded code. We
derive a heuristic upper bound on the failure probability of the probabilistic
unique decoder and verify the results via Monte Carlo simulations.
