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Found 5 papers, 4 papers with code
PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model
To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates.
PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model
The techniques used to develop a PINN surrogate of the SPM are extended in Part II for the PINN surrogate for the P2D battery model, and explore the Bayesian calibration capabilities of both surrogates.
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets
Recent advances in modeling large-scale complex physical systems have shifted research focuses towards data-driven techniques.
GANISP: a GAN-assisted Importance SPlitting Probability Estimator
Genealogical importance splitting reduces the variance of rare event probability estimators by iteratively selecting and replicating realizations that are headed towards a rare event.
Adversarial sampling of unknown and high-dimensional conditional distributions
In that case, it is necessary to sample elements from unknown high-dimensional spaces with possibly millions of degrees of freedom.
