Model Discovery

Model Discovery is the process of uncovering partial differential equations (PDEs) from spatiotemporal data, aiming to automatically identify the mathematical models that describe physical phenomena through data analysis and machine learning techniques. This task falls under the Miscellaneous category, with the goal of enhancing the accuracy and generalization capability of the models, thereby providing deeper insights and predictive power in fields such as fluid mechanics and materials science.