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The identification of the governing equations of chaotic dynamical systems from data has recently emerged as a hot topic.
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Arnaud Doucet and Adam M Johansen, · 2009
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Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, and Lawrence Carin, · 2016
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Marco Fraccaro, Sø ren Kaae Sø nderby, Ulrich Paquet, and Ole Winther, · 2016
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“Using Machine Learning to Replicate Chaotic Attractors and Calculate Lyapunov Exponents from Data,”
Jaideep Pathak, Zhixin Lu, Brian R. Hunt, Michelle Girvan, and Edward Ott, · 2017
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“Filtering Variational Objectives,”
Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet, and Yee Whye Teh, · 2017
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Ronan Fablet, Said Ouala, and Cedric Herzet, · 2017
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Differential equations, dynamical systems, and an introduction to chaos
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“Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems,”
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Maziar Raissi, · 2018
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“Data Driven Governing Equations Approximation Using Deep Neural Networks,”
Tong Qin, Kailiang Wu, and Dongbin Xiu, · 2018
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“Deep learning algorithm for data-driven simulation of noisy dynamical system,”
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