1.2k citations · 3.1k across the 36 of their papers we have counts for
4 papers · 1 filter
Efficient Automatic Differentiation of Implicit Functions
Charles C. Margossian, Michael Betancourt
Derivative-based algorithms are ubiquitous in statistics, machine learning, and applied mathematics. Automatic differentiation offers an algorithmic way to efficiently evaluate the…
A Short Review of Ergodicity and Convergence of Markov chain Monte Carlo Estimators
Michael Betancourt
This short note reviews the basic theory for quantifying both the asymptotic and preasymptotic convergence of Markov chain Monte Carlo estimators.
A Unifying and Canonical Description of Measure-Preserving Diffusions
Alessandro Barp, So Takao, Michael Betancourt +2
A complete recipe of measure-preserving diffusions in Euclidean space was recently derived unifying several MCMC algorithms into a single framework. In this paper, we develop a geo…
Workflow Techniques for the Robust Use of Bayes Factors
Daniel J. Schad, Bruno Nicenboim, Paul-Christian Bürkner +2
Inferences about hypotheses are ubiquitous in the cognitive sciences. Bayes factors provide one general way to compare different hypotheses by their compatibility with the observed…