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Artificial Intelligence for Modeling and Simulation (AIMS) Lab

RESEARCH BLOG

Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator

Aug 13, 20241 min read

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Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator

Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator

Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation

Aug 13, 20241 min read

77 views

Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation

Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation

Neural Dynamical Operator with Gradient-Based and Derivative-Free Optimization Methods

Aug 13, 20241 min read

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Neural Dynamical Operator with Gradient-Based and Derivative-Free Optimization Methods

Neural Dynamical Operator with Gradient-Based and Derivative-Free Optimization Methods

Learning About Structural Errors in Models of Complex Dynamical Systems

Aug 13, 20242 min read

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Learning About Structural Errors in Models of Complex Dynamical Systems

Learning About Structural Errors in Models of Complex Dynamical Systems

Causation Entropy Boosting

Aug 13, 20242 min read

27 views

Causation Entropy Boosting

Causation Entropy Boosting

Learning Stochastic Closures Using Ensemble Kalman Inversion

Oct 29, 20212 min read

468 views

Learning Stochastic Closures Using Ensemble Kalman Inversion

Learning Stochastic Closures Using Ensemble Kalman Inversion

Epidemic Management and Control Through Risk-Dependent Individual Contact Interventions

Oct 29, 20212 min read

195 views

Epidemic Management and Control Through Risk-Dependent Individual Contact Interventions

Epidemic Management and Control Through Risk-Dependent Individual Contact Interventions

Ensemble Kalman Inversion for Sparse Learning of Dynamical Systems from Time-Averaged Data

Oct 29, 20211 min read

269 views

Ensemble Kalman Inversion for Sparse Learning of Dynamical Systems from Time-Averaged Data

Ensemble Kalman Inversion for Sparse Learning of Dynamical Systems from Time-Averaged Data

Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical

Oct 29, 20212 min read

157 views

Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical

Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical

Physics-informed machine learning approach for augmenting turbulence models

Nov 8, 20182 min read

454 views

Physics-informed machine learning approach for augmenting turbulence models

Physics-informed machine learning approach for augmenting turbulence models

Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies

Nov 8, 20181 min read

385 views

Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies

Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies

Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations

Nov 8, 20182 min read

188 views

Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations

Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations

Seeing permeability from images: fast prediction with convolutional neural networks

Nov 2, 20181 min read

231 views

Seeing permeability from images: fast prediction with convolutional neural networks

Seeing permeability from images: fast prediction with convolutional neural networks

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