neural-operators
The case against using transformers for physics News
Caltech's Anima Anandkumar argues that simulating the physical world at industrial resolution implies hundreds of billions to a trillion tokens of context, putting it permanently out of reach for transformers -- and that neural operators, which learn maps between functions rather than sequences, are already outrunning supercomputers on weather, climate and fusion.
Neural operators Lesson
A neural operator learns a mapping between whole functions rather than between fixed-size arrays, which lets one trained model work at any grid resolution and makes learned physics simulation orders of magnitude faster than solving the equations.
neuraloperator Tool
The open-source PyTorch library for Fourier neural operators and related architectures -- the toolkit behind FourCastNet and the plasma and lithography surrogates. If you want to try learning a solution operator for a PDE instead of solving it step by step, this is the reference implementation.