Pages that link to "Item:Q137310"

The following pages link to Discovering governing equations from data by sparse identification of nonlinear dynamical systems (Q137310):

Displaying 50 items.

• Model selection for hybrid dynamical systems via sparse regression (Q4973922) (← links)
• Reduced-order modelling of the flow around a high-lift configuration with unsteady Coanda blowing (Q4976719) (← links)
• From snapshots to modal expansions – bridging low residuals and pure frequencies (Q4976790) (← links)
• Variational Inference Formulation for a Model-Free Simulation of a Dynamical System with Unknown Parameters by a Recurrent Neural Network (Q4986840) (← links)
• Sparsity-promoting algorithms for the discovery of informative Koopman-invariant subspaces (Q4987934) (← links)
• Galerkin force model for transient and post-transient dynamics of the fluidic pinball (Q4989062) (← links)
• Data-driven resolvent analysis (Q4989070) (← links)
• Kernel-based parameter estimation of dynamical systems with unknown observation functions (Q4989104) (← links)
• 9 From the POD-Galerkin method to sparse manifold models (Q4993250) (← links)
• Reduced-order models for coupled dynamical systems: Data-driven methods and the Koopman operator (Q4993714) (← links)
• Data-Driven Learning of Nonautonomous Systems (Q4997352) (← links)
• (Q4998909) (← links)
• (Q4998931) (← links)
• Probabilistic solutions to DAEs learning from physical data (Q5016828) (← links)
• Generalized Cell Mapping Method with Deep Learning for Global Analysis and Response Prediction of Dynamical Systems (Q5016866) (← links)
• Reduced order model approach for imaging with waves (Q5019927) (← links)
• Augmenting physical models with deep networks for complex dynamics forecasting* (Q5020055) (← links)
• Cluster-based hierarchical network model of the fluidic pinball – cartographing transient and post-transient, multi-frequency, multi-attractor behaviour (Q5022961) (← links)
• A Nonautonomous Equation Discovery Method for Time Signal Classification (Q5024512) (← links)
• Blind Identification of Stochastic Block Models from Dynamical Observations (Q5027031) (← links)
• Concurrent MultiParameter Learning Demonstrated on the Kuramoto--Sivashinsky Equation (Q5038404) (← links)
• Equation discovery from data: promise and pitfalls, from rabbits to Mars (Q5039484) (← links)
• Numerical Identification of Nonlocal Potentials in Aggregation (Q5042005) (← links)
• Learning Low-Dimensional Dynamical-System Models from Noisy Frequency-Response Data with Loewner Rational Interpolation (Q5049221) (← links)
• What Machine Learning Can Do for Computational Solid Mechanics (Q5051038) (← links)
• (Q5054631) (← links)
• Data-driven robust tracking control of underactuated mechanical systems using identified flat output and active disturbance rejection control (Q5056548) (← links)
• Koopman Linear Quadratic Regulator Using Complex Eigenfunctions for Nonlinear Dynamical Systems (Q5056846) (← links)
• Discretization of parameter identification in PDEs using neural networks (Q5058109) (← links)
• Extracting stochastic dynamical systems with α-stable Lévy noise from data (Q5066035) (← links)
• <i>A priori</i> sparsification of Galerkin models (Q5074575) (← links)
• Robust Identification of Differential Equations by Numerical Techniques from a Single Set of Noisy Observation (Q5075698) (← links)
• Modern Koopman Theory for Dynamical Systems (Q5075835) (← links)
• The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation (Q5096451) (← links)
• Asymptotic Theory of \(\boldsymbol \ell _1\) -Regularized PDE Identification from a Single Noisy Trajectory (Q5097857) (← links)
• On the Koopman Operator of Algorithms (Q5109369) (← links)
• Time-Delay Observables for Koopman: Theory and Applications (Q5109371) (← links)
• Physics-Informed Probabilistic Learning of Linear Embeddings of Nonlinear Dynamics with Guaranteed Stability (Q5109771) (← links)
• Prediction Accuracy of Dynamic Mode Decomposition (Q5112644) (← links)
• Learning partial differential equations for biological transport models from noisy spatio-temporal data (Q5114254) (← links)
• On the structure of time-delay embedding in linear models of non-linear dynamical systems (Q5129835) (← links)
• The<i>l</i>₁-based sparsification of energy interactions in unsteady lid-driven cavity flow (Q5131427) (← links)
• Extracting Structured Dynamical Systems Using Sparse Optimization With Very Few Samples (Q5137942) (← links)
• Topologically Based Fractional Diffusion and Emergent Dynamics with Short-Range Interactions (Q5139103) (← links)
• The structure of reconstructed flows in latent spaces (Q5139746) (← links)
• Discovering transition phenomena from data of stochastic dynamical systems with Lévy noise (Q5139747) (← links)
• Learning latent dynamics for partially observed chaotic systems (Q5139802) (← links)
• Extracting non-Gaussian governing laws from data on mean exit time (Q5140882) (← links)
• Detecting the maximum likelihood transition path from data of stochastic dynamical systems (Q5140892) (← links)
• Interpreting neural network models of residual scalar flux (Q5144568) (← links)