Author

Jing-Yang Tan

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#machine learning Jul 2026

Interval and fuzzy physics-augmented neural networks (iPANN and fPANN) for uncertainty quantification and propagation in constitutive modeling

The proposed framework provides a compact, physics-consistent route for distribution-free aleatoric uncertainty quantification in hyperelastic constitutive modeling, and propagation in downstream finite element simulations.

S. P. Singh, G. Padmanabha, Jing-Yang Tan et al. · arXiv.org · 0 citations