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Solving the Elastic Wave Equation with Physics-Informed Neural Networks: A Robust and Critical Assessment
Physics-Informed Neural Networks (PINNs) have recently emerged as a promising approach for solving Partial Differential Equations (PDEs), offering a meshfree alternative that integrates physical principles into the learning process. This presents a new paradigm compared to traditional discretization methods and purely data-driven machine learning techniques. While promising, PINNs are not a panacea; they inherit challenges such as spectral bias and unstable convergence. Moreover, their potential in seismology remains largely unexplored. In this work, we provide a robust and critical assessment
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-07T21:01:29.000Z
First collected: 2026-09-20T20:32:20.942Z. This is not the publication date.