6 citations · 18 across the 9 of their papers we have counts for
4 papers · 1 filter
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…
Bayesian inferences on uncertain ranks and orderings: Application to ranking players and lineups
Andres F. Barrientos, Deborshee Sen, Garritt L Page +1
It is common to be interested in rankings or order relationships among entities. In complex settings where one does not directly measure a univariate statistic upon which to base r…
Efficient posterior sampling for high-dimensional imbalanced logistic regression
Deborshee Sen, Matthias Sachs, Jianfeng Lu +1
High-dimensional data are routinely collected in many areas. We are particularly interested in Bayesian classification models in which one or more variables are imbalanced. Current…
Posterior Projection for Inference in Constrained Spaces
Lachlan Astfalck, Deborshee Sen, Sayan Patra +2
Estimation of parameters that obey specific constraints is crucial in statistics and machine learning; for example, when parameters are required to satisfy boundedness, monotonicit…