WGFINNs use weak-form loss functions with GENERIC structure preservation to recover governing equations more accurately from noisy observations than prior strong-form GFINNs.
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WGFINNs: Weak formulation-based GENERIC formalism informed neural networks
WGFINNs use weak-form loss functions with GENERIC structure preservation to recover governing equations more accurately from noisy observations than prior strong-form GFINNs.