1 citations · 1 across the 2 of their papers we have counts for
3 papers
stat.ME2021
Scalable Bayesian inference for time series via divide-and-conquer
Rihui Ou, Lachlan Astfalck, Deborshee Sen +1
Bayesian computational algorithms tend to scale poorly as data size increases. This has motivated divide-and-conquer-based approaches for scalable inference. These divide the data…
stat.ME2021
Bayesian inference on high-dimensional multivariate binary responses
Antik Chakraborty, Rihui Ou, David B. Dunson
It has become increasingly common to collect high-dimensional binary response data; for example, with the emergence of new sampling techniques in ecology. In smaller dimensions, mu…
stat.ML2018★ 1 cited
Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent states
Rihui Ou, Deborshee Sen, Alexander L Young +1
Markov chain Monte Carlo (MCMC) algorithms for hidden Markov models often rely on the forward-backward sampler. This makes them computationally slow as the length of the time serie…