102 citations · 251 across the 16 of their papers we have counts for
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stat.ML2019
Challenges in Markov chain Monte Carlo for Bayesian neural networks
Theodore Papamarkou, Jacob Hinkle, M. Todd Young +1
Markov chain Monte Carlo (MCMC) methods have not been broadly adopted in Bayesian neural networks (BNNs). This paper initially reviews the main challenges in sampling from the para…
stat.CO2019★ 95 cited
Distributions.jl: Definition and Modeling of Probability Distributions in the JuliaStats Ecosystem
Mathieu Besançon, Theodore Papamarkou, David Anthoff +4
Random variables and their distributions are a central part in many areas of statistical methods. The Distributions.jl package provides Julia users and developers tools for working…