INI-VPINN is a new weak-form PINN formulation that implicitly enforces Neumann and interface conditions for Poisson and Laplace problems in multi-material domains with geometric singularities.
An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications
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math.NA 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Holomorphic neural networks enforce exact satisfaction of harmonic PDEs for 3D Laplace and elasticity problems using Whittaker representations and boundary-only training.
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INI-VPINN: A Variational Physics-Informed Neural Network with Implicit Neumann and Interface Handling for Multi-Material Domains with Geometric Singularities
INI-VPINN is a new weak-form PINN formulation that implicitly enforces Neumann and interface conditions for Poisson and Laplace problems in multi-material domains with geometric singularities.
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A holomorphic neural network framework for 3D boundary value problems governed by harmonic potentials
Holomorphic neural networks enforce exact satisfaction of harmonic PDEs for 3D Laplace and elasticity problems using Whittaker representations and boundary-only training.