Machine Learning

We use machine learning algorithms to parameterize models to make useful predictions from theoretical and experimental data.  Examples include predicting new experimental conditions for high-yield catalysis and developing parameterized approximations for electronic structure methods.  Chemistry has a long and rich history of using parameterization from data to understand the world around us and machine learning is the modern continuation of this tradition.