most citedConditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation

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cs.LG2024★ 1 cited

GenAI4UQ: A Software for Inverse Uncertainty Quantification Using Conditional Generative Models

Ming Fan, Zezhong Zhang, Dan Lu +1

We introduce GenAI4UQ, a software package for inverse uncertainty quantification in model calibration, parameter estimation, and ensemble forecasting in scientific applications. Ge…

cs.LG2024★ 2 cited

Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation

Minglei Yang, Pengjun Wang, Ming Fan +3

We introduce a conditional pseudo-reversible normalizing flow for constructing surrogate models of a physical model polluted by additive noise to efficiently quantify forward and i…