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V. Kalinin

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Open access Oct 2026

MultiPINN: A Modular Framework for Physics-Informed Neural Networks

Physics-informed neural networks (PINNs) approximate solutions of differential equations by embedding governing equations and boundary conditions into the training objective. Controlled PINN comparisons are difficult because geometry representation, collocation sampling, loss construction, neural architecture, and opti...

C. Tsgoev, V. Kalinin, M. Bratenkov et al. · 0 citations

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