A novel physics-regularized interpretable machine learning model for grain growth

•A new computational model based on machine learning is developed to model grain growth.•Two-dimensional simulation results are validated with analytical models.•Large-scale simulations showed a steady-state behavior and matched with previous simulation results.•Ability to learn irregular grain growth is also demonstrated.