ALP Seminar: Physical inductive biases for learning simulation and scientific discovery

This talk will explore both how our knowledge of physics can improve our machine learning approaches, and how our machine learning tools can be used to improve our knowledge of physics. I'll describe work my collaborators and I have done using particle- and mesh-based approaches for learning simulation, how we leverage inductive biases about ODEs, Hamiltonian and Lagrangian mechanics in learned simulators, and how we can use neural networks with symbolic regression to discover physical governing equations from simulated and real data.