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Open access Jul 2026

A gradient-enhanced physics-informed neural network with adaptive loss weighting for high-dimensional non-linear sine-Gordon problems.

When the proposed method is compared to state-of-the-art variants of PINN, it is established that the method is superior to the current methods in a variety of high-dimensional PDEs with very small error magnitudes, even in the 20D case.

Alemayehu Tamirie Deresse, T. Dufera · 0 citations