2 citations · 4 across the 2 of their papers we have counts for
3 papers · 1 filter
Temporal Subsampling Diminishes Small Spatial Scales in Recurrent Neural Network Emulators of Geophysical Turbulence
Timothy A. Smith, Stephen G. Penny, Jason A. Platt +1
The immense computational cost of traditional numerical weather and climate models has sparked the development of machine learning (ML) based emulators. Because ML methods benefit…
Constraining Chaos: Enforcing dynamical invariants in the training of recurrent neural networks
Jason A. Platt, Stephen G. Penny, Timothy A. Smith +2
Drawing on ergodic theory, we introduce a novel training method for machine learning based forecasting methods for chaotic dynamical systems. The training enforces dynamical invari…
`Next Generation' Reservoir Computing: an Empirical Data-Driven Expression of Dynamical Equations in Time-Stepping Form
Tse-Chun Chen, Stephen G. Penny, Timothy A. Smith +1
Next generation reservoir computing based on nonlinear vector autoregression (NVAR) is applied to emulate simple dynamical system models and compared to numerical integration schem…