The optimization of conical intersection structures is
complicated
by the nondifferentiability of the adiabatic potential energy surfaces.
In this work, we build a pseudodiabatic surrogate model, based on
Gaussian process regression, formed by three smooth and differentiable
surfaces that can adequately reproduce the adiabatic surfaces. Using
this model with the restricted variance optimization method results
in a notable decrease of the overall computational effort required
to obtain minimum energy crossing points.