2 citations · 3 across the 3 of their papers we have counts for
3 papers
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…
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation
Yanfang Liu, Minglei Yang, Zezhong Zhang +3
We present a supervised learning framework of training generative models for density estimation. Generative models, including generative adversarial networks, normalizing flows, va…
A pseudo-reversible normalizing flow for stochastic dynamical systems with various initial distributions
Minglei Yang, Pengjun Wang, Diego del-Castillo-Negrete +2
We present a pseudo-reversible normalizing flow method for efficiently generating samples of the state of a stochastic differential equation (SDE) with different initial distributi…