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physics.geo-ph2026
Differentiable Graph Neural Network Simulator for the Back-Analysis of Post-Liquefaction Residual Strength from Flow Failure Runout
Yongjin Choi, Jorge Macedo
This study introduces Differentiable Graph Neural Network Simulators (Diff-GNS) as a physics-informed and automated framework for estimating post-liquefaction residual strengths ($…
physics.geo-ph2025
Differentiable graph neural network simulator for forward and inverse modeling of multi-layered slope system with multiple material properties
Yongjin Choi, Jorge Macedo, Chenying Liu
Graph neural network simulators (GNS) have emerged as a computationally efficient tool for simulating granular flows. Previous efforts have been limited to simplified homogeneous g…