Q.‐C. He

Predictive Modeling with Learned Constitutive Laws from Indirect Observations

Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences

Advances in understanding hydration of Portland cement

Dependence of compressive strength on phase assemblage in cement pastes: Beyond gel–space ratio — Experimental evidence and micromechanical modeling

Physics-informed machine learning

VASPKIT: A user-friendly interface facilitating high-throughput computing and analysis using VASP code

Learning constitutive relations using symmetric positive definite neural networks

Comment on ‘The Computational 2D Materials Database: high-throughput modeling and discovery of atomically thin crystals’

Influence of inclusion shapes on the effective linear elastic properties of hardened cement pastes

Computational homogenization of nonlinear elastic materials using neural networks

On the symmetries of 2D elastic and hyperelastic tensors