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insight - Neural Network Approximation of PDEs
Overcoming the Curse of Dimensionality in Neural Network Approximation of PDEs
Deep neural networks can overcome the curse of dimensionality in approximating solutions of certain nonlinear PDEs.
Adversarial Adaptive Sampling: Unifying PINN and Optimal Transport for PDE Approximation at ICLR 2024
提案されたAdversarial Adaptive Sampling（AAS）アプローチは、PDEのニューラルネットワーク近似においてPINNと最適輸送を統合しました。
Adaptive Finite Element Interpolated Neural Networks Analysis
Neural networks are used to approximate partial differential equations with local phenomena, introducing adaptive finite element interpolated neural networks.
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