5 papers
Stochastic Gradient Descent for Semilinear Elliptic Equations with Uncertainties
Ting Wang, Jaroslaw Knap
Randomness is ubiquitous in modern engineering. The uncertainty is often modeled as random coefficients in the differential equations that describe the underlying physics. In this…
Convergence of the likelihood ratio method for linear response of non-equilibrium stationary states
Petr Plechac, Gabriel Stoltz, Ting Wang
We consider numerical schemes for computing the linear response of steady-state averages of stochastic dynamics with respect to a perturbation of the drift part of the stochastic d…
Accelerated scale bridging with sparsely approximated Gaussian learning
Ting Wang, Kenneth W. Leiter, Petr Plechac +1
Multiscale modeling is a systematic approach to describe the behavior of complex systems by coupling models from different scales. The approach has been demonstrated to be very eff…
On the Validity of the Girsanov Transformation Method for Sensitivity Analysis of Stochastic Chemical Reaction Networks
Ting Wang, Muruhan Rathinam
We investigate the validity of the Girsanov Transformation (GT) method for parametric sensitivity analysis of stochastic models of chemical reaction networks. The validity depends…
Steady State Sensitivity Analysis of Continuous Time Markov Chains
Ting Wang, Petr Plechac
In this paper we study Monte Carlo estimators based on the likelihood ratio approach for steady-state sensitivity. We first extend the result of Glynn and Olvera-Cravioto [doi:doi:…