4 papers
SOMA: A Novel Sampler for Bayesian Inference from Privatized Data
Yifei Xiong, Nianqiao Phyllis Ju
Making valid statistical inferences from privatized data is a key challenge in modern analysis. In Bayesian settings, data augmentation MCMC (DAMCMC) methods impute unobserved conf…
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods
Xiliang Yang, Yifei Xiong, Zhijian He
There is a growing interest in studying sequential neural posterior estimation (SNPE) techniques due to their advantages for simulation-based models with intractable likelihoods. T…
Simulation-based Bayesian Inference from Privacy Protected Data
Yifei Xiong, Nianqiao Phyllis Ju, Sanguo Zhang
Many modern statistical analysis and machine learning applications require training models on sensitive user data. Under a formal definition of privacy protection, differentially p…
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation
Yifei Xiong, Xiliang Yang, Sanguo Zhang +1
Sequential neural posterior estimation (SNPE) techniques have been recently proposed for dealing with simulation-based models with intractable likelihoods. Unlike approximate Bayes…