Machine learning and data-driven methods
How can we use large amounts of data for fast and reliable predictions in case where the underlying physical phenomena remain poorly understood or where computer simulation of these phenomena with classical methods would be prohibitively expensive?
We are addressing this question in the following areas
Multi-fidelity methods for combining computer simulations and machine learning
Constitutive Artificial Neural Networks (CANNs)