Locally adaptive activation functions with slope recovery for deep and physics-informed neural networks

Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems

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Adaptive activation functions accelerate convergence in deep and physics-informed neural networks

(2019) Ameya D. Jagtap et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Adaptive activation functions in convolutional neural networks

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Method of relaxed streamline upwinding for hyperbolic conservation laws

(2018) Ameya D. Jagtap   WAVE MOTION

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

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The extreme learning machine learning algorithm with tunable activation function

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