AI RESEARCH
An End-to-End PyTorch Interface for Differentiable PDE Solvers: A RANS Model-Correction Study
arXiv CS.LG
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ArXi:2605.28858v1 Announce Type: cross This work presents an end-to-end strategy for solving inverse problems constrained by Partial Differential Equations within a fully differentiable Machine Learning framework. The proposed formulation provides a unified and user-friendly methodology applicable to a wide range of problems, from data assimilation to closure modeling.