A PINN-DeepONet framework for extracting turbulent combustion closure from multiscalar measurements

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Nature Machine Intelligence · 2021 · 2.8K citations · Full text

Computing, Computer Science, Mathematics +10

Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-PLUS Illustrations

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When and why PINNs fail to train: A neural tangent kernel perspective

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Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems

Tianping Chen, Hong Chen · IEEE Transactions on Neural Networks · 1995 · 1.2K citations

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On reduced mechanisms for methaneair combustion in nonpremixed flames

R.W. Bilger, S.H. Stårner, Robert J. Kee · Combustion and Flame · 1990 · 862 citations

Engineering, Chemical Engineering, Mechanical Engineering +16