activity
20172023
most citedA backward Monte-Carlo method for time-dependent runaway electron simulations

23 citations · 35 across the 6 of their papers we have counts for

collaborators

11 papers

math.OC20237 cited

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.…

math.NA20221 cited

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…

physics.comp-ph2021

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…

cs.LG2021

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…

cs.LG20213 cited

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…

physics.app-ph2020

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…