Information-distilled physics informed deep learning for high order differential inverse problems with extreme discontinuities. [PDF]
Peng M, Tang H.
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Scientific Machine Learning for Elastic and Acoustic Wave Propagation: Neural Operator and Physics-Guided Neural Network. [PDF]
Mehtaj N, Banerjee S.
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Inf-sup stable space-time Local Discontinuous Galerkin method for the heat equation. [PDF]
Gómez S, Perinati C, Stocker P.
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Gradient-Driven Physics Informed Neural Networks for Conduction Heat Transfer and Incompressible Laminar Flow. [PDF]
Lu T +5 more
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From PINNs to PIKANs: recent advances in physics-informed machine learning. [PDF]
Toscano JD +6 more
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Random Neural Networks for Rough Volatility. [PDF]
Jacquier A, Žurič Ž.
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Assessment of Spatially-Varying Arterial Wall Stiffness and Pressure Using a Physics-Informed Neural Network and Pulse Wave Imaging: An in Silico and Experimental Phantom Study of Stenotic Vessels. [PDF]
Roy T +4 more
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New modifications of ADM with applications in kind of PDEs. [PDF]
Nemah EM, Jaddoa AF, Ghazi FF.
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Fast electromagnetic field simulation using a current-density- based physics-informed neural network. [PDF]
Gao Z +5 more
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Fast adaptation of physics-informed hybrid models for pneumatic artificial muscles. [PDF]
Wang G, Chalard R, Cifuentes J, Pham MT.
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