Controlling Chaos in Van Der Pol Dynamics Using Signal-Encoded Deep Learning

Physics-Informed Neural Networks for Optimal Planar Orbit Transfers

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Physics-Informed Neural Network for High Frequency Noise Performance in Quasi-Ballistic MOSFETs

(2021) Jonghwan Lee   Electronics

Physics-informed learning of governing equations from scarce data

(2021) Zhao Chen et al.   Nature Communications

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

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Solving complex optimal control problems with nonlinear controls using trigonometric functions

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Automatic differentiation for error analysis of Monte Carlo data

(2019) Alberto Ramos   COMPUTER PHYSICS COMMUNICATIONS

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 learning

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Optimal feedback control of the forced van der Pol system

(2012) T.P. Chagas et al.   CHAOS SOLITONS & FRACTALS

Design principles of biochemical oscillators

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Biological applications of the “Filtered” Van der Pol oscillator

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