4 papers
Inverse Gaussian Process regression for likelihood-free inference
Hongqiao Wang, Ziqiao Ao, Tengchao Yu +1
In this work we consider Bayesian inference problems with intractable likelihood functions. We present a method to compute an approximate of the posterior with a limited number of…
Bayesian optimization with local search
Yuzhou Gao, Tengchao Yu, Jinglai Li
Global optimization finds applications in a wide range of real world problems. The multi-start methods are a popular class of global optimization techniques, which are based on the…
Maximum conditional entropy Hamiltonian Monte Carlo sampler
Tengchao Yu, Hongqiao Wang, Jinglai Li
The performance of Hamiltonian Monte Carlo (HMC) sampler depends critically on some algorithm parameters such as the total integration time and the numerical integration stepsize.…
A weight-bounded importance sampling method for variance reduction
Tengchao Yu, Linjun Lu, Jinglai Li
Importance sampling (IS) is an important technique to reduce the estimation variance in Monte Carlo simulations. In many practical problems, however, the use of IS method may resul…