Pages that link to "Item:Q2124010"
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The following pages link to Data-driven discovery of coarse-grained equations (Q2124010):
Displaying 13 items.
- Data-driven molecular modeling with the generalized Langevin equation (Q2124588) (← links)
- Extended dynamic mode decomposition for inhomogeneous problems (Q2132641) (← links)
- Data-driven discovery of multiscale chemical reactions governed by the law of mass action (Q2134528) (← links)
- Explicit physics-informed neural networks for nonlinear closure: the case of transport in tissues (Q2136464) (← links)
- Information geometry of physics-informed statistical manifolds and its use in data assimilation (Q2162022) (← links)
- Machine learning of nonlocal micro-structural defect evolutions in crystalline materials (Q2679512) (← links)
- Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker--Planck Equation and Physics-Informed Neural Networks (Q5004999) (← links)
- Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models (Q5022489) (← links)
- Data-driven discovery of governing equations for fluid dynamics based on molecular simulation (Q5222604) (← links)
- Data-Driven Discovery of Governing Equations for Coarse-Grained Heterogeneous Network Dynamics (Q6076413) (← links)
- Data-Driven Discovery of Coarse-Grained Equations (Q6334041) (← links)
- Data-driven models of nonautonomous systems (Q6553794) (← links)
- Ml-GLE: a machine learning enhanced generalized Langevin equation framework for transient anomalous diffusion in polymer dynamics (Q6589873) (← links)
