1.2k citations · 3.1k across the 36 of their papers we have counts for
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stat.ME2013★ 65 cited
Hamiltonian Monte Carlo for Hierarchical Models
M. J. Betancourt, Mark Girolami
Hierarchical modeling provides a framework for modeling the complex interactions typical of problems in applied statistics. By capturing these relationships, however, hierarchical…
stat.ME2013★ 32 cited
Generalizing the No-U-Turn Sampler to Riemannian Manifolds
M. J. Betancourt
Hamiltonian Monte Carlo provides efficient Markov transitions at the expense of introducing two free parameters: a step size and total integration time. Because the step size contr…