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Artificial Intelligence for Modeling and Simulation (AIMS) Lab

RESEARCH BLOG

Aug 13, 20241 min read

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

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

Aug 13, 20241 min read

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

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

Aug 13, 20241 min read

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

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

Aug 13, 20242 min read

Learning About Structural Errors in Models of Complex Dynamical Systems

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Learning About Structural Errors in Models of Complex Dynamical Systems

Aug 13, 20242 min read

Causation Entropy Boosting

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Causation Entropy Boosting

Oct 29, 20212 min read

Learning Stochastic Closures Using Ensemble Kalman Inversion

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Learning Stochastic Closures Using Ensemble Kalman Inversion

Oct 29, 20212 min read

Epidemic Management and Control Through Risk-Dependent Individual Contact Interventions

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Epidemic Management and Control Through Risk-Dependent Individual Contact Interventions

Oct 29, 20211 min read

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

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

Oct 29, 20212 min read

Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical

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Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical

Nov 8, 20182 min read

Physics-informed machine learning approach for augmenting turbulence models

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Physics-informed machine learning approach for augmenting turbulence models

Nov 8, 20181 min read

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

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

Nov 8, 20182 min read

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

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

Nov 2, 20181 min read

Seeing permeability from images: fast prediction with convolutional neural networks

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Seeing permeability from images: fast prediction with convolutional neural networks

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