Learning local features and high frequencies is an important problem in Scientific Machine Learning. For instance, effectively modeling turbulence (e.g., $Re=3500$ and above) depends on accurately...

The use of machine learning to estimate the energy of a group of atoms, and the forces that drive them to more stable configurations, have revolutionized the fields of computational chemistry and mate...

Transferability of atom-based neural networks, Frederik Ø Kjeldal, Janus J Eriksen

Transferability of atom-based neural networks, Frederik Ø Kjeldal, Janus J Eriksen

We introduce an approach for imposing physically informed inductive biases in learned simulation models. We combine graph networks with a differentiable ordinary differential equation integrator as a ...