φ-DeepONet learns mappings with discontinuities in inputs and outputs by combining multiple branch networks with a nonlinear interface embedding in the trunk, trained via physics- and interface-informed loss, and shows accurate results on 1D/2D benchmarks.
Application of the finite-element method to the diffusion and reaction of chemical species in multilayered polymeric bodies.Mathematical Modelling, 7(2-3):385–395
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$\phi-$DeepONet: A Discontinuity Capturing Neural Operator
φ-DeepONet learns mappings with discontinuities in inputs and outputs by combining multiple branch networks with a nonlinear interface embedding in the trunk, trained via physics- and interface-informed loss, and shows accurate results on 1D/2D benchmarks.