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…
Inferring the unknown parameters in Differential Equation by Gaussian Process Regression with Constraint
Ying Zhou, Hongqiao Wang
Differential Equation (DE) is a commonly used modeling method in various scientific subjects such as finance and biology. The parameters in DE models often have interesting scienti…
Explicit Estimation of Derivatives from Data and Differential Equations by Gaussian Process Regression
Hongqiao Wang, Xiang Zhou
In this work, we employ the Bayesian inference framework to solve the problem of estimating the solution and particularly, its derivatives, which satisfy a known differential equat…
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.…