2 citations · 9 across the 17 of their papers we have counts for
5 papers · 1 filter
IEnSF: Iterative Ensemble Score Filter for Reducing Error in Posterior Score Estimation in Nonlinear Data Assimilation
Zezhong Zhang, Feng Bao, Guannan Zhang
The Ensemble Score Filter (EnSF) is a score-based diffusion model approach for solving high-dimensional and nonlinear data assimilation problems. While initial applications of EnSF…
A Score-based Diffusion Model Approach for Adaptive Learning of Stochastic Partial Differential Equation Solutions
Toan Huynh, Ruth Lopez Fajardo, Guannan Zhang +2
We propose a novel framework for adaptively learning the time-evolving solutions of stochastic partial differential equations (SPDEs) using score-based diffusion models within a re…
On the sensitivity of different ensemble filters to the type of assimilated observation networks
Zixiang Xiong, Siming Liang, Feng Bao +2
Recent advances in data assimilation (DA) have focused on developing more flexible approaches that can better accommodate nonlinearities in models and observations. However, it rem…
Diffusion-based supervised learning of generative models for efficient sampling of multimodal distributions
Hoang Tran, Zezhong Zhang, Feng Bao +2
We propose a hybrid generative model for efficient sampling of high-dimensional, multimodal probability distributions for Bayesian inference. Traditional Monte Carlo methods, such…
Ensemble score filter with image inpainting for data assimilation in tracking surface quasi-geostrophic dynamics with partial observations
Siming Liang, Hoang Tran, Feng Bao +3
Data assimilation plays a pivotal role in understanding and predicting turbulent systems within geoscience and weather forecasting, where data assimilation is used to address three…