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A deep (convolutional) neural network is trained to predict the ground-state energy of an electron in two-dimensional potentials. The machinery of deep learning is developed to learn the mapping between potential and energy, which bypasses the need to numerically solve the Schr\"odinger equation and the need for computing wave functions.
Mills et al. (Wed,) studied this question.