  We implement a pseudolikelyhood approach with l2-regularization as well as
the recently introduced pseudolikelihood with decimation procedure to the
inverse problem in continuous spin models on arbitrary networks, with
arbitrarily disordered couplings. Performances of the approaches are tested
against data produced by Monte Carlo numerical simulations and compared also
from previously studied fully-connected mean-field-based inference techniques.
The results clearly show that the best network reconstruction is obtained
through the decimation scheme, that also allows to dwell the inference down to
lower temperature regimes. Possible applications to phasor models for light
propagation in random media are proposed and discussed.
