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Distributions.jl: definition and modeling of probability distributions in the JuliaStats ecosystem

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 with probability distributions, leveraging Julia features for their …

Wide neural networks with bottlenecks are deep Gaussian processes

There has recently been much work on the 'wide limit' of neural networks, where Bayesian neural networks (BNNs) are shown to converge to a Gaussian process (GP) as all hidden layers are sent to infinite width. However, these results do not apply to …

The controlled thermodynamic integral for Bayesian model evidence evaluation

Approximation of the model evidence is well known to be challenging. One promising approach is based on thermodynamic integration, but a key concern is that the thermodynamic integral can suffer from high variability in many applications. This …

RNA editing generates cellular subsets with diverse sequence within populations

RNA editing is a mutational mechanism that specifically alters the nucleotide content in transcribed RNA. However, editing rates vary widely, and could result from equivalent editing amongst individual cells, or represent an average of variable …

Zero variance differential geometric Markov chain Monte Carlo algorithms

Differential geometric Markov Chain Monte Carlo (MCMC) strategies exploit the geometry of the target to achieve convergence in fewer MCMC iterations at the cost of increased computing time for each of the iterations. Such computational complexity is …