Delay differential equations (DDEs) extend the classical framework of differential equations by incorporating terms that depend on past states, thus capturing the intrinsic time delays found in many ...
Physics-informed neural networks (PINNs) represent a burgeoning paradigm in computational science, whereby deep learning frameworks are augmented with explicit physical laws to solve both forward and ...
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