3 papers
cs.LG2025
JAX-MPM: A Learning-Augmented Differentiable Meshfree Framework for GPU-Accelerated Lagrangian Simulation and Geophysical Inverse Modeling
Honghui Du, QiZhi He
Differentiable programming has emerged as a powerful paradigm in scientific computing, enabling automatic differentiation through simulation pipelines and naturally supporting both…
cs.LG2025
History-Aware Neural Operator: Robust Data-Driven Constitutive Modeling of Path-Dependent Materials
Binyao Guo, Zihan Lin, QiZhi He
This study presents an end-to-end learning framework for data-driven modeling of path-dependent inelastic materials using neural operators. The framework is built on the premise th…
cs.LG2024
Differentiable Neural-Integrated Meshfree Method for Forward and Inverse Modeling of Finite Strain Hyperelasticity
Honghui Du, Binyao Guo, QiZhi He
The present study aims to extend the novel physics-informed machine learning approach, specifically the neural-integrated meshfree (NIM) method, to model finite-strain problems cha…