25 citations · 85 across the 11 of their papers we have counts for
11 papers
A Score-based Nonlinear Filter for Data Assimilation
Feng Bao, Zezhong Zhang, Guannan Zhang
We introduce a score-based generative sampling method for solving the nonlinear filtering problem with robust accuracy. A major drawback of existing nonlinear filtering methods, e.…
A probabilistic scheme for semilinear nonlocal diffusion equations with volume constraints
Minglei Yang, Guannan Zhang, Diego Del-Castillo-Negrete +1
This work presents a probabilistic scheme for solving semilinear nonlocal diffusion equations with volume constraints and integrable kernels. The nonlocal model of interest is defi…
A Feynman-Kac based numerical method for the exit time probability of a class of transport problems
Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete +1
The exit time probability, which gives the likelihood that an initial condition leaves a prescribed region of the phase space of a dynamical system at, or before, a given time, is…
A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models
Jiaxin Zhang, Sirui Bi, Guannan Zhang
Bayesian experimental design (BED) aims at designing an experiment to maximize the information gathering from the collected data. The optimal design is usually achieved by maximizi…
A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Models
Jiaxin Zhang, Sirui Bi, Guannan Zhang
Bayesian experimental design (BED) is to answer the question that how to choose designs that maximize the information gathering. For implicit models, where the likelihood is intrac…
A directional Gaussian smoothing optimization method for computational inverse design in nanophotonics
Jiaxin Zhang, Sirui Bi, Guannan Zhang
Local-gradient-based optimization approaches lack nonlocal exploration ability required for escaping from local minima in non-convex landscapes. A directional Gaussian smoothing (D…
A sparse-grid probabilistic scheme for approximation of the runaway probability of electrons in fusion tokamak simulation
Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete +2
Runaway electrons (RE) generated during magnetic disruptions present a major threat to the safe operation of plasma nuclear fusion reactors. A critical aspect of understanding RE d…
Robust data-driven approach for predicting the configurational energy of high entropy alloys
Jiaxin Zhang, Xianglin Liu, Sirui Bi +3
High entropy alloys (HEAs) have been increasingly attractive as promising next-generation materials due to their various excellent properties. It's necessary to essentially charact…
Non-intrusive inference reduced order model for fluids using linear multistep neural network
Xuping Xie, Guannan Zhang, Clayton G. Webster
In this effort we propose a data-driven learning framework for reduced order modeling of fluid dynamics. Designing accurate and efficient reduced order models for nonlinear fluid d…
A fluid-kinetic framework for self-consistent runaway-electron simulations
Eero Hirvijoki, Chang Liu, Guannan Zhang +2
The problem of self-consistently coupling kinetic runaway-electron physics to the macroscopic evolution of the plasma is addressed by dividing the electron population into a bulk a…
A backward Monte-Carlo method for time-dependent runaway electron simulations
Guannan Zhang, Diego del-Castillo-Negrete
Kinetic descriptions of runaway electrons (RE) are usually based on Fokker-Planck models that determine the probability distribution function (PDF) of RE in 2-dimensional momentum…