Transformers in The Loop
Scaling learned Lagrangian models to larger simulations using transformer architectures.
Graph convolutions are inherently local, which bounds how far information can travel in a single step. Transformers offer a route to longer-range interactions in learned particle models, at the cost of a much harder scaling problem.
Work in progress.