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20212026
most citedOn physics-informed data-driven isotropic and anisotropic constitutive models through probabilistic machine learning and space-filling sampling

130 citations · 549 across the 28 of their papers we have counts for

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physics.comp-ph2026

Mixture of Polyconvex Neural Potentials for Parametric Hyperelasticity: Towards Foundation Material Models

Steven J. Yang, Govinda Anantha Padmanabha, D. Thomas Seidl +1

Hyperelastic constitutive models enable modeling large deformations in elastic solids. In common practice, a strain energy density function is prescribed in advance and model-speci…