3 citations · 3 across the 4 of their papers we have counts for
6 papers
Diffusion-Based Stochastic Operator Networks for Uncertainty Quantification in Stochastic Partial Differential Equations
Phuoc-Toan Huynh, Richard Archibald, Feng Bao
We introduce a novel framework for uncertainty quantification of solution operators associated with stochastic partial differential equations (SPDEs). Although SPDEs play a central…
Finite Expression Method with TranNet-based Function Learning for High-Dimensional Partial Differential Equations
Phuoc-Toan Huynh, Feng Bao, Haizhao Yang +1
In this paper, we study a machine-learning-based solver for high-dimensional partial differential equations (PDEs). Computing accurate solutions efficiently for such problems remai…
A Score Filter Enhanced Data Assimilation Framework for Data-Driven Dynamical Systems
Jingqiao Tang, Ryan Bausback, Feng Bao +2
We introduce a score-filter-enhanced data assimilation framework designed to reduce predictive uncertainty in machine learning (ML) models for data-driven dynamical system forecast…
Joint State-Parameter Estimation for the Reduced Fracture Model via the United Filter
Toan Huynh, Thi-Thao-Phuong Hoang, Guannan Zhang +1
In this paper, we introduce an effective United Filter method for jointly estimating the solution state and physical parameters in flow and transport problems within fractured poro…
Parameter Estimation for the Reduced Fracture Model via a Direct Filter Method
Phuoc Toan Huynh, Feng Bao, Thi-Thao-Phuong Hoang
In this work, we present a numerical method that provides accurate real-time detection for the widths of the fractures in a fractured porous medium based on observational data on p…
Fast and accurate domain decomposition methods for reduced fracture models with nonconforming time grids
Phuoc-Toan Huynh, Yanzhao Cao, Thi-Thao-Phuong Hoang
This paper is concerned with the numerical solution of compressible fluid flow in a fractured porous medium. The fracture represents a fast pathway (i.e., with high permeability) a…