9 citations · 23 across the 12 of their papers we have counts for
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3 papers · 1 filter
stat.CO2016★ 2 cited
A fully Bayesian strategy for high-dimensional hierarchical modeling using massively parallel computing
Will Landau, Jarad Niemi
Markov chain Monte Carlo (MCMC) is the predominant tool used in Bayesian parameter estimation for hierarchical models. When the model expands due to an increasing number of hierarc…
stat.CO2013
Massively parallel approximate Gaussian process regression
Robert B. Gramacy, Jarad Niemi, Robin M. Weiss
We explore how the big-three computing paradigms -- symmetric multi-processor (SMC), graphical processing units (GPUs), and cluster computing -- can together be brought to bare on…
stat.CO2011★ 4 cited
Efficient Bayesian inference in stochastic chemical kinetic models using graphical processing units
Jarad Niemi, Matthew Wheeler
A goal of systems biology is to understand the dynamics of intracellular systems. Stochastic chemical kinetic models are often utilized to accurately capture the stochastic nature…