116 citations · 305 across the 40 of their papers we have counts for
6 papers · 1 filter
On an adaptive preconditioned Crank-Nicolson MCMC algorithm for infinite dimensional Bayesian inferences
Zixi Hu, Zhewei Yao, Jinglai Li
Many scientific and engineering problems require to perform Bayesian inferences for unknowns of infinite dimension. In such problems, many standard Markov Chain Monte Carlo (MCMC)…
A Derivative-Free Trust-Region Algorithm for Reliability-Based Optimization
Tian Gao, Jinglai Li
In this note, we present a derivative-free trust-region (TR) algorithm for reliability based optimization (RBO) problems. The proposed algorithm consists of solving a set of subpro…
A TV-Gaussian prior for infinite-dimensional Bayesian inverse problems and its numerical implementations
Zhewei Yao, Zixi Hu, Jinglai Li
Many scientific and engineering problems require to perform Bayesian inferences in function spaces, in which the unknowns are of infinite dimension. In such problems, choosing an a…
Gaussian process surrogates for failure detection: a Bayesian experimental design approach
Hongqiao Wang, Guang Lin, Jinglai Li
An important task of uncertainty quantification is to identify {the probability of} undesired events, in particular, system failures, caused by various sources of uncertainties. In…
A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification
Keyi Wu, Jinglai Li
In this work we consider a class of uncertainty quantification problems where the system performance or reliability is characterized by a scalar parameter . The performance para…
An adaptive independence sampler MCMC algorithm for infinite dimensional Bayesian inferences
Zhe Feng, Jinglai Li
Many scientific and engineering problems require to perform Bayesian inferences in function spaces, in which the unknowns are of infinite dimension. In such problems, many standard…