Investigating KAN-Based Physics-Informed Neural Networks for EMI/EMC Simulations
<|reference_start|>Investigating KAN-Based Physics-Informed Neural Networks for EMI/EMC Simulations: The main objective of this paper is to investigate the feasibility of employing Physics-Informed Neural Networks (PINNs) techniques, in particular KolmogorovArnold Networks (KANs), for facilitating Electromagnetic Interference (EMI) simulations. It introduces some common EM problem formulations and how they can be solved using AI-driven solutions instead of lengthy and complex full-wave numerical simulations. This research may open new horizons for green EMI simulation workflows with less energy consumption and feasible computational capacity.<|reference_end|>
@article{qian2024investigating,
    title={Investigating KAN-Based Physics-Informed Neural Networks for EMI/EMC
  Simulations},
    author={Kun Qian and Mohamed Kheir},
    journal={arXiv preprint arXiv:2405.11383},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.11383},
    primaryClass={cs.LG}
}