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Updated: Jan 7, 2026

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Representación vs. optimización: Entrenamiento de PINNs y PIKANs para el descubrimiento de caja gris en farmacología

Nazanin Ahmadi Daryakenari¹, Khemraj Shukla², George Em Karniadakis²

¹Center for Biomedical Engineering, Brown University, Providence, RI 02912, USA.

Computers in biology and medicine

|December 25, 2025

Resumen

Las Redes de Kolmogorov-Arnold Informadas por la Física (PIKANs) ofrecen una alternativa a las Redes Neuronales Informadas por la Física (PINNs) para la identificación de sistemas. Este estudio compara PIKANs y PINNs, proporcionando orientación sobre optimizadores y arquitecturas para mejorar la modelización de caja gris en farmacología de sistemas.

Sus antecedentes:

Physics-Informed Neural Networks (PINNs) and Physics-Informed Kolmogorov-Arnold Networks (PIKANs) are used for inverse problems and gray-box system identification.
A comprehensive understanding of PIKANs' performance compared to PINNs is lacking.

Conclusiones:

The study offers practical guidance for selecting optimizers and architectures for robust and efficient gray-box discovery in systems pharmacology.
Findings contribute to improving the training of physics-informed networks in systems pharmacology, systems biology, and related fields.

Palabras clave:

redes de kolmogorov-arnold PIKANs PINNs Farmacometría Biología de sistemas Farmacología de sistemas

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