Tuesday, November 20, 2018
12:50PM - 1:03PM
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Q01.00001: Data-driven reduced modeling of turbulent convection using DMD-enhanced Fluctuation-Dissipation Theorem
Pedram Hassanzadeh, Mohammad Amin Khodkar
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Tuesday, November 20, 2018
1:03PM - 1:16PM
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Q01.00002: Why is the cylinder flow a terrible test case for deep learning?
Jean-Christophe Loiseau
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Tuesday, November 20, 2018
1:16PM - 1:29PM
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Q01.00003: Deep learning of dynamics and signal-noise decomposition with time-stepping constraints
Samuel Rudy, Nathan Kutz, Steven L Brunton
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Tuesday, November 20, 2018
1:29PM - 1:42PM
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Q01.00004: Sparse identification of nonlinear dynamics for model predictive control in the low-data limit
Eurika Kaiser, J. Nathan Kutz, Steven L Brunton
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Tuesday, November 20, 2018
1:42PM - 1:55PM
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Q01.00005: Recovering Quasi-2D Navier-Stokes Model Parameters via Weak Formulation
Patrick Reinbold, Roman O Grigoriev
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Tuesday, November 20, 2018
1:55PM - 2:08PM
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Q01.00006: Koopman mode expansions between two invariant sets
Jacob Page, Rich Kerswell
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Tuesday, November 20, 2018
2:08PM - 2:21PM
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Q01.00007: Abstract Withdrawn
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Tuesday, November 20, 2018
2:21PM - 2:34PM
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Q01.00008: Control-oriented model learning with a recurrent neural network
Michele Alessandro Bucci, Onofrio Semeraro, Alexandre Allauzen, Laurent Cordier, Guillaume Wisniewski, Lionel Mathelin
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Tuesday, November 20, 2018
2:34PM - 2:47PM
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Q01.00009: Nonlinear integro-differential operator regression with neural networks
Ravi G Patel, Olivier Desjardins
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Tuesday, November 20, 2018
2:47PM - 3:00PM
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Q01.00010: Control-Informed Dynamic Mode Decomposition
Michael J Banks, Daniel Joseph Bodony
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Tuesday, November 20, 2018
3:00PM - 3:13PM
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Q01.00011: Improvements on Extended Kalman Filter Dynamic Mode Decomposition for Noisy Dataset
Taku Nonomura
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Tuesday, November 20, 2018
3:13PM - 3:26PM
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Q01.00012: Reduced Order Control using Low-Rank Dynamic Mode Decomposition
Palash Sashittal, Daniel Joseph Bodony
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