Combining speed and accuracy in computational chemistry: Machine learning for short-range interactions augmented by physical models at long-range Ghent University
Statistical-learning approaches are emerging as powerful alternatives to expensive computational
methods for solving the Schrödinger equation to determine molecular properties. Despite the
recent success of methods like neural networks, these models are only suitable for interpolation
and fail to scale to larger systems. That is, when a model is trained on small-to-medium-size
molecules, it can only be applied to ...