Pages that link to "Item:Q5157694"
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The following pages link to Weak SINDy: Galerkin-Based Data-Driven Model Selection (Q5157694):
Displaying 24 items.
- Stabilized neural ordinary differential equations for long-time forecasting of dynamical systems (Q2112549) (← links)
- Weak SINDy for partial differential equations (Q2132599) (← links)
- Learning biological dynamics from spatio-temporal data by Gaussian processes (Q2141319) (← links)
- Learning mean-field equations from particle data using WSINDy (Q2167982) (← links)
- Reconstruction of delay differential equations via learning parameterized dictionary (Q2688070) (← links)
- WeakIdent: weak formulation for identifying differential equation using narrow-fit and trimming (Q2699369) (← links)
- Equation discovery from data: promise and pitfalls, from rabbits to Mars (Q5039484) (← links)
- Data-driven sparse identification of nonlinear dynamical systems using linear multistep methods (Q6042122) (← links)
- Model selection via reweighted partial sparse recovery (Q6056227) (← links)
- Learning sparse nonlinear dynamics via mixed-integer optimization (Q6060066) (← links)
- Auxiliary functions as Koopman observables: data-driven analysis of dynamical systems via polynomial optimization (Q6066022) (← links)
- Data-Driven Discovery of Governing Equations for Coarse-Grained Heterogeneous Network Dynamics (Q6076413) (← links)
- Direct estimation of parameters in ODE models using WENDy: weak-form estimation of nonlinear dynamics (Q6078313) (← links)
- Group projected subspace pursuit for identification of variable coefficient differential equations (GP-IDENT) (Q6087946) (← links)
- Derivative-based SINDy (DSINDy): addressing the challenge of discovering governing equations from noisy data (Q6099213) (← links)
- Sparse identification of dynamical systems by reweighted \(l_1\)-regularized least absolute deviation regression (Q6121816) (← links)
- Structured model selection via ℓ1−ℓ2 optimization (Q6141559) (← links)
- Convergence of weak-SINDy surrogate models (Q6492266) (← links)
- Adaptive integral alternating minimization method for robust learning of nonlinear dynamical systems from highly corrupted data (Q6553634) (← links)
- The occupation kernel method for nonlinear system identification (Q6555693) (← links)
- Physics-informed genetic programming for discovery of partial differential equations from scarce and noisy data (Q6589933) (← links)
- On higher order drift and diffusion estimates for stochastic SINDy (Q6592244) (← links)
- On the identifiability of nonlocal interaction kernels in first-order systems of interacting particles on Riemannian manifolds (Q6620727) (← links)
- Forecasting and predicting stochastic agent-based model data with biologically-informed neural networks (Q6632673) (← links)
