Rihui Ou

I am a PhD student in statistics at Duke University. I work with Prof. David Dunson. My current research interests include but not limited to scalable Bayesian inference, Bayesian nonparametric models and factor models. I seek to develop efficient Bayesian methods that can be scalable to "large n" and "large p" with guarantees. Before coming to Duke, I obtained my bachelor's degree at Zhejiang University. I am best reached by: rihui.ou [at] duke.edu.

Publications and Preprints

• Ou, R., Sen, D., & Dunson, D. (2021). Scalable Bayesian inference for time series via divide-and-conquer. [arXiv].

• Chakraborty, A., Ou, R., & Dunson, D. B. (2021). Bayesian inference on high-dimensional multivariate binary data. [arXiv]

• Ou, R., Sen, D., Young, A.L., & Dunson, D. (2021). Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent states. [arXiv]