Pages that link to "Item:Q5161393"

The following pages link to Model Reduction with Memory and the Machine Learning of Dynamical Systems (Q5161393):

Displaying 29 items.

• Multi-level dynamical systems: connecting the Ruelle response theory and the Mori-Zwanzig approach (Q358672) (← links)
• Applied unsupervised learning in model reduction of linear dynamic systems (Q679283) (← links)
• Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism (Q777576) (← links)
• Problem reduction, renormalization, and memory (Q855016) (← links)
• Memory-based reduced modelling and data-based estimation of opinion spreading (Q2022637) (← links)
• Dimension reduction in recurrent networks by canonicalization (Q2076953) (← links)
• Error bounds of the invariant statistics in machine learning of ergodic Itô diffusions (Q2077623) (← links)
• Kernel-based prediction of non-Markovian time series (Q2077859) (← links)
• Machine learning for prediction with missing dynamics (Q2128320) (← links)
• Analytic continuation of noisy data using Adams Bashforth residual neural network (Q2129155) (← links)
• Effective Mori-Zwanzig equation for the reduced-order modeling of stochastic systems (Q2129159) (← links)
• Dynamically learning the parameters of a chaotic system using partial observations (Q2155717) (← links)
• PDE-Net 2.0: learning PDEs from data with a numeric-symbolic hybrid deep network (Q2222627) (← links)
• The deep learning Galerkin method for the general Stokes equations (Q2674271) (← links)
• NySALT: Nyström-type inference-based schemes adaptive to large time-stepping (Q2683252) (← links)
• An online manifold learning approach for model reduction of dynamical systems (Q2927840) (← links)
• <i>A priori</i> estimation of memory effects in reduced-order models of nonlinear systems using the Mori–Zwanzig formalism (Q4557142) (← links)
• (Q5054645) (← links)
• Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units (Q5162006) (← links)
• Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks (Q5162358) (← links)
• Using machine learning to predict extreme events in complex systems (Q5854795) (← links)
• Simultaneous neural network approximation for smooth functions (Q6052416) (← links)
• A framework for machine learning of model error in dynamical systems (Q6076655) (← links)
• Regression-Based Projection for Learning Mori–Zwanzig Operators (Q6084965) (← links)
• Learning Theory for Dynamical Systems (Q6132792) (← links)
• Memory-based parameterization with differentiable solver: application to Lorenz '96 (Q6549988) (← links)
• Shock trace prediction by reduced models for a viscous stochastic Burgers equation (Q6561716) (← links)
• A dynamical systems approach to machine learning (Q6564359) (← links)
• Ml-GLE: a machine learning enhanced generalized Langevin equation framework for transient anomalous diffusion in polymer dynamics (Q6589873) (← links)