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04/28/2023
Temporal Subsampling Diminishes Small Spatial Scales in Recurrent Neural Network Emulators of Geophysical Turbulence
The immense computational cost of traditional numerical weather and clim...
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04/24/2023
Constraining Chaos: Enforcing dynamical invariants in the training of recurrent neural networks
Drawing on ergodic theory, we introduce a novel training method for mach...
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01/21/2022
A Systematic Exploration of Reservoir Computing for Forecasting Complex Spatiotemporal Dynamics
A reservoir computer (RC) is a type of simplified recurrent neural netwo...
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01/13/2022
`Next Generation' Reservoir Computing: an Empirical Data-Driven Expression of Dynamical Equations in Time-Stepping Form
Next generation reservoir computing based on nonlinear vector autoregres...
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09/25/2021
Integrating Recurrent Neural Networks with Data Assimilation for Scalable Data-Driven State Estimation
Data assimilation (DA) is integrated with machine learning in order to p...
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02/04/2021
Forecasting Using Reservoir Computing: The Role of Generalized Synchronization
Reservoir computers (RC) are a form of recurrent neural network (RNN) us...
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11/19/2019
