  Scar theory is one of the fundamental pillars in the field of quantum chaos,
and scarred functions a superb tool to carry out studies in it. Several
methods, usually semiclassical, have been described to cope with these two
phenomena. In this paper, we present an alternative method, based on the novel
machine learning algorithm known as Reservoir Computing, to calculate such
scarred wavefunctions together with the associated eigenstates of the system.
The resulting methodology achieves outstanding accuracy while reducing
execution times by a factor of ten. As an illustration of the effectiveness of
this method, we apply it to the widespread chaotic two-dimensional coupled
quartic oscillator.
