Physics-Informed Neural Plasticity: PDE Solvers That Reshape Themselves

Physics-Informed Neural Plasticity introduces a method where neural network representations change during optimization based on physics errors. The ReCAP solver dynamically adapts its capacity by enriching, pruning, merging, or splitting components locally where physics is complex. This allows solvers to use the right amount of representation capacity precisely where it is needed.

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