Pages that link to "Item:Q5137942"
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The following pages link to Extracting Structured Dynamical Systems Using Sparse Optimization With Very Few Samples (Q5137942):
Displaying 23 items.
- Generalization bounds for sparse random feature expansions (Q2105118) (← links)
- SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations (Q2128325) (← links)
- PDE-Net 2.0: learning PDEs from data with a numeric-symbolic hybrid deep network (Q2222627) (← links)
- Unsupervised discovery of interpretable hyperelastic constitutive laws (Q2237006) (← links)
- WeakIdent: weak formulation for identifying differential equation using narrow-fit and trimming (Q2699369) (← links)
- (Q3002949) (← links)
- Extracting Sparse High-Dimensional Dynamics from Limited Data (Q4561658) (← links)
- Weak SINDy: Galerkin-Based Data-Driven Model Selection (Q5157694) (← links)
- Discovery of Nonlinear Multiscale Systems: Sampling Strategies and Embeddings (Q5382442) (← links)
- (Q5383427) (← links)
- Learning Dynamical Systems with Side Information (Q5883299) (← links)
- Data-driven sparse identification of nonlinear dynamical systems using linear multistep methods (Q6042122) (← links)
- Model selection via reweighted partial sparse recovery (Q6056227) (← links)
- A framework for machine learning of model error in dynamical systems (Q6076655) (← links)
- A Bayesian framework for learning governing partial differential equation from data (Q6090678) (← links)
- Discovering stochastic partial differential equations from limited data using variational Bayes inference (Q6118584) (← links)
- Kernel functions embed into the autoencoder to identify the sparse models of nonlinear dynamics (Q6121868) (← links)
- Structured model selection via ℓ1−ℓ2 optimization (Q6141559) (← links)
- Learning dynamical systems from data: a simple cross-validation perspective. V: Sparse kernel flows for 132 chaotic dynamical systems (Q6496480) (← links)
- A proximal alternating direction method of multipliers for DC programming with structured constraints (Q6536834) (← links)
- Learning nonparametric ordinary differential equations from noisy data (Q6553789) (← links)
- Hausdorff metric based training of kernels to learn attractors with application to 133 chaotic dynamical systems (Q6558876) (← links)
- A discretization-invariant extension and analysis of some deep operator networks (Q6633297) (← links)
