5.7k citations · 12k across the 78 of their papers we have counts for
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Automatic monotonicity detection for Gaussian Processes
Eero Siivola, Juho Piironen, Aki Vehtari
We propose a new method for automatically detecting monotonic input-output relationships from data using Gaussian Process (GP) models with virtual derivative observations. Our resu…
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria
Marko Järvenpää, Michael Gutmann, Aki Vehtari +1
Approximate Bayesian computation (ABC) can be used for model fitting when the likelihood function is intractable but simulating from the model is feasible. However, even a single e…
On the Hyperprior Choice for the Global Shrinkage Parameter in the Horseshoe Prior
Juho Piironen, Aki Vehtari
The horseshoe prior has proven to be a noteworthy alternative for sparse Bayesian estimation, but as shown in this paper, the results can be sensitive to the prior choice for the g…
Chained Gaussian Processes
Alan D. Saul, James Hensman, Aki Vehtari +1
Gaussian process models are flexible, Bayesian non-parametric approaches to regression. Properties of multivariate Gaussians mean that they can be combined linearly in the manner o…
Bayesian aggregation of average data: An application in drug development
Sebastian Weber, Andrew Gelman, Daniel Lee +3
Throughout the different phases of a drug development program, randomized trials are used to establish the tolerability, safety, and efficacy of a candidate drug. At each stage one…