Author

Xiaomei Yang

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Preprint Sep 2026

Exact Likelihood-Coin Poisson Sampling for Bayesian Inverse Problems with Sharp Complexity Bounds

We develop an exact posterior-sampling framework for Bayesian inverse problems when selected bounded forward observables can be accessed through Bernoulli events. A Bernstein--Poisson construction converts these forward coins into scaled Gaussian likelihood coins, and thinning an inflated prior Poisson point process yi...

Zhi-Liang Deng, Xiao-Mei Yang · 0 citations

Preprint Sep 2026

Likelihood-Coin Poisson Sampling for Bayesian Inverse Problems: Exact Sampling and Sharp Complexity

We develop an exact direct-sampling framework for Bayesian inverse problems whose bounded forward observables can be queried through Bernoulli events rather than numerically evaluated. A Bernstein--Poisson construction converts these events into scaled Gaussian likelihood coins. Thinning a prior-based Poisson point pro...

Zhi-Liang Deng, Xiao-Mei Yang · 1 citation

Preprint Aug 2026

Posterior Convergence without Force Convergence: Resolution-Stable Sampling for Rough Bayesian Inverse Problems

Bayesian targets may converge under model refinement even when the exact sensitivities used by gradient-based samplers do not. We study this probability--sensitivity mismatch and its consequences for Metropolized Hamiltonian proposals. A vanishing-amplitude wiggly-energy model first gives the basic analytic obstruction...

Zhi-Liang Deng, Xiao-Mei Yang · 0 citations