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Learning PDE solution operators with variable initial conditions via Latent Dynamics Networks

Stefano Maria Pizzamiglio et al.
arXiv CS · Papers
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machine-learningneural-networks
In many-query scenarios, data-driven surrogate models provide an efficient alternative to high-fidelity solvers for simulating physical systems governed by Partial Differential Equations (PDEs). In this context, the Latent Dynamics Network (LDNet) has recently demonstrated remarkable performance in
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