Information-distilled physics informed deep learning for high order differential inverse problems with extreme discontinuities. [PDF]
Peng M, Tang H.
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A deep neural network model for heat transfer in darcy-forchheimer hybrid nanofluid flow with activation energy. [PDF]
Ayman-Mursaleen M +4 more
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Physics-Informed Emulation of Systemic Circulation for Fast Parameter Estimation and Uncertainty Quantification. [PDF]
Ryan W +4 more
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Time fractional modeling of MHD natural convection flow between parallel plates via caputo-fabrizio integral. [PDF]
Masood K.
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SOR-Based numerical modeling of hybrid nanofluid flow over a rotating disk with magneto-nonlinear radiation and arrhenius activation energy considering shape factors. [PDF]
Ahmad A +5 more
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Automatic network structure discovery of physics informed neural networks via knowledge distillation. [PDF]
Liu Z +6 more
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Physics-informed extreme learning machine (PIELM) for consolidation around an expanded cylindrical cavity. [PDF]
Pang CQ +4 more
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Transient flow and heat transfer of CuO-Al<sub>2</sub>O<sub>3</sub>/H<sub>2</sub>O hybrid nanofluid flow over a radially stretching surface with dissipation and ohmic heating. [PDF]
Ragavi M, Poornima T, Sreenivasulu P.
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