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We employ adaptive activation functions for regression in deep and physics-informed neural networks (PINNs) to approximate smooth and discontinuous functions as well as solutions of linear and nonlinear partial differential equations.
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2019
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M. Raissi, P. Perdikaris, G.E. Karniadakis, Physics-informed neural network: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. J. Comput. Phys., 378, 686-707, 2019
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