"GINN-KAN: Interpretability pipelining with applications in Physics ..."

Nisal Ranasinghe et al. (2024)

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DOI: 10.48550/ARXIV.2408.14780

access: open

type: Informal or Other Publication

metadata version: 2024-09-28

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  - journals/corr/abs-2408-14780
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  - https://dblp.org/rec/journals/corr/abs-2408-14780
Nisal Ranasinghe, Yu Xia, Sachith Seneviratne, Saman K. Halgamuge:
GINN-KAN: Interpretability pipelining with applications in Physics Informed Neural Networks. CoRR abs/2408.14780 (2024)

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