  The use of deep learning in physical sciences has recently boosted the
ability of researchers to tackle physical systems where little or no analytical
insight is available. Recently, the Physics-Informed Neural Networks (PINNs)
have been introduced as one of the most promising tools to solve systems of
differential equations guided by some physically grounded constraints. In the
quantum realm, such approach paves the way to a novel approach to solve the
Schroedinger equation for non-integrable systems. By following an unsupervised
learning approach, we apply the PINNs to the anharmonic oscillator in which an
interaction term proportional to the fourth power of the position coordinate is
present. We compute the eigenenergies and the corresponding eigenfunctions
while varying the weight of the quartic interaction. We bridge our solutions to
the regime where both the perturbative and the strong coupling theory work,
including the pure quartic oscillator. We investigate systems with real and
imaginary frequency, laying the foundation for novel numerical methods to
tackle problems emerging in quantum field theory.
