Tag: PINNs

CFD

This paper proposes a periodic activation function architecture using complex exponential to generate paired sine and cosine outputs, demonstrating improved performance over sine-activated MLPs for reconstructing convective flows in physics-informed neural networks.

ScientificML

This paper proposes an improved periodic activation using complex exponential functions generating paired sine-cosine outputs for Physics-Informed Neural Networks, demonstrating superior performance over sine-activated MLPs in reconstructing temperature fields from sparse velocity data in convective flows.