The following pages link to I. G. Kevrekidis (Q271675):
Displaying 45 items.
- (Q5703086) (← links)
- VORTICES IN BOSE–EINSTEIN CONDENSATES: SOME RECENT DEVELOPMENTS (Q5704677) (← links)
- Equation‐free optimal switching policies for bistable reacting systems (Q5704778) (← links)
- (Q5708137) (← links)
- Accuracy of Patch Dynamics with Mesoscale Temporal Coupling for Efficient Massively Parallel Simulations (Q5739949) (← links)
- Deciding the Nature of the Coarse Equation through Microscopic Simulations: The Baby-Bathwater Scheme (Q5757484) (← links)
- Virtual Slow Manifolds: The Fast Stochastic Case (Q5851445) (← links)
- Characterization of a two-parameter mixed-mode electrochemical behavior regime using neural networks (Q5937260) (← links)
- A computer-assisted study of pulse dynamics in anisotropic media (Q5940280) (← links)
- GANs and Closures: Micro-Macro Consistency in Multiscale Modeling (Q6051545) (← links)
- Discrete-time nonlinear feedback linearization via physics-informed machine learning (Q6078485) (← links)
- Physics-agnostic and physics-infused machine learning for thin films flows: modelling, and predictions from small data (Q6086911) (← links)
- Learning dynamical systems from data: a simple cross-validation perspective. IV: Case with partial observations (Q6096532) (← links)
- Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data (Q6110192) (← links)
- A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms (Q6154930) (← links)
- Double diffusion maps and their latent harmonics for scientific computations in latent space (Q6158080) (← links)
- To Infinity and Beyond: Some ODE and PDE Case Studies (Q6277957) (← links)
- Extended dynamic mode decomposition with dictionary learning: a data-driven adaptive spectral decomposition of the Koopman operator (Q6288533) (← links)
- Linking Machine Learning with Multiscale Numerics: Data-Driven Discovery of Homogenized Equations (Q6347747) (← links)
- Staying the course: Locating equilibria of dynamical systems on Riemannian manifolds defined by point-clouds (Q6397144) (← links)
- Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles (Q6397898) (← links)
- Data-driven Control of Agent-based Models: an Equation/Variable-free Machine Learning Approach (Q6404766) (← links)
- From partial data to out-of-sample parameter and observation estimation with Diffusion Maps and Geometric Harmonics (Q6424584) (← links)
- Gentlest ascent dynamics on manifolds defined by adaptively sampled point-clouds (Q6425899) (← links)
- Learning Parametric Koopman Decompositions for Prediction and Control (Q6453428) (← links)
- Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era (Q6456526) (← links)
- Machine Learning for the identification of phase-transitions in interacting agent-based systems (Q6457122) (← links)
- Equation-Free Dynamic Renormalization: Self-Similarity in Multidimensional Particle System Dynamics (Q6475511) (← links)
- Multiscale analysis of re-entrant production lines: An equation-free approach (Q6476302) (← links)
- Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks (Q6522497) (← links)
- Intelligent Attractors for Singularly Perturbed Dynamical Systems (Q6523248) (← links)
- Data-driven cold starting of good reservoirs (Q6526271) (← links)
- Initializing LSTM internal states via manifold learning (Q6556957) (← links)
- Hausdorff metric based training of kernels to learn attractors with application to 133 chaotic dynamical systems (Q6558876) (← links)
- Learning the temporal evolution of multivariate densities via normalizing flows (Q6560595) (← 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)
- Self-similar blow-up solutions in the generalised Korteweg-de Vries equation: spectral analysis, normal form and asymptotics (Q6592190) (← links)
- Tipping points of evolving epidemiological networks: machine learning-assisted, data-driven effective modeling (Q6592553) (← links)
- Implementation and (inverse modified) error analysis for implicitly templated ODE-nets (Q6629683) (← links)
- Data-driven cold starting of good reservoirs (Q6629745) (← links)
- Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification (Q6639348) (← links)
- RandONets: shallow networks with random projections for learning linear and nonlinear operators (Q6648362) (← links)
- Thinner Latent Spaces: Detecting dimension and imposing invariance through autoencoder gradient constraints (Q6742165) (← links)
- Gaussian Processes simplify differential equations (Q6746785) (← links)
