Near-term quantum computers provide a promising platform for finding the ground states of systems, which is an essential task in physics, chemistry and materials science. However, near-term approaches are constrained by effects noise, as well limited resources hardware. We introduce neural error mitigation, uses networks to improve estimates ground-state observables obtained using simulations. ...