Pages that link to "Item:Q1742825"
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The following pages link to Parsimonious representation of nonlinear dynamical systems through manifold learning: a chemotaxis case study (Q1742825):
Displaying 22 items.
- Dimensionality reduction of collective motion by principal manifolds (Q282231) (← links)
- Dimensionality reduction of complex metastable systems via kernel embeddings of transition manifolds (Q2022651) (← links)
- Equation-free patch scheme for efficient computational homogenisation via self-adjoint coupling (Q2055980) (← links)
- Numerical bifurcation analysis of PDEs from lattice Boltzmann model simulations: a parsimonious machine learning approach (Q2149520) (← links)
- A geometric heat-flow theory of Lagrangian coherent structures (Q2190705) (← links)
- Manifold learning for accelerating coarse-grained optimization (Q2194441) (← links)
- Data-driven control of agent-based models: an equation/variable-free machine learning approach (Q2687520) (← links)
- Data-Driven Reduction for a Class of Multiscale Fast-Slow Stochastic Dynamical Systems (Q3188143) (← links)
- Manifold learning for organizing unstructured sets of process observations (Q3303828) (← links)
- Kernel-based parameter estimation of dynamical systems with unknown observation functions (Q4989104) (← links)
- Deep learning models for global coordinate transformations that linearise PDEs (Q5014841) (← links)
- (Q5053320) (← links)
- Spectral Discovery of Jointly Smooth Features for Multimodal Data (Q5070856) (← links)
- Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian (Q5143283) (← links)
- Grassmannian diffusion maps based surrogate modeling via geometric harmonics (Q6070089) (← links)
- Physics-agnostic and physics-infused machine learning for thin films flows: modelling, and predictions from small data (Q6086911) (← links)
- Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data (Q6110192) (← links)
- Double diffusion maps and their latent harmonics for scientific computations in latent space (Q6158080) (← links)
- Initializing LSTM internal states via manifold learning (Q6556957) (← links)
- Time-series forecasting using manifold learning, radial basis function interpolation, and geometric harmonics (Q6567586) (← links)
- Learning effective stochastic differential equations from microscopic simulations: linking stochastic numerics to deep learning (Q6572673) (← links)
- Tipping points of evolving epidemiological networks: machine learning-assisted, data-driven effective modeling (Q6592553) (← links)
