AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A quantum spectral method for non-periodic boundary value problems with arbitrary Dirichlet boundary conditions is presented, which extends the recently proposed approach by Liu et al. (2024), in which periodic problems are discretised using truncated Fourier series.
This work proposes two neural operator architectures that directly map experimentally measured data to the constitutive functions governing the mechanical response of the material: Physics-Augmented Neural Operators (PANO) and Constitutive Artificial Neural Operators (CANO).
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