  Within an artificial neural network (ANN) approach, we classify simulated
signals corresponding to the semi-classical description of Bloch oscillations
on a two-dimensional square lattice. After the ANN is properly trained, we
consider the inverse problem of Bloch oscillations (BO) in which a new signal
is classified according to the lattice spacing and external electric field
strength oriented along a particular direction of the lattice with an accuracy
of 96%. This approach can be improved depending on the time spent in training
the network and the computational power available. This work is one of the
first efforts for analyzing the BO with ANN in two-dimensional crystals.
