Sorin Liviu Jurj

Physics Structure-Informed Neural Networks in the TinyML Pipeline: Antisymmetry Preservation, Deployment Accounting, and Training-Budget Sensitivity

The results separate what physics structure preserves from what TinyML deployment must measure explicitly, as structure improves Burgers accuracy and antisymmetry at a given footprint rather than automatically shrinking hardware requirements.