7 citations · 21 across the 12 of their papers we have counts for
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Several Remarks on the Numerical Integrator in Lagrangian Monte Carlo
James A. Brofos, Roy R. Lederman
Riemannian manifold Hamiltonian Monte Carlo (RMHMC) is a powerful method of Bayesian inference that exploits underlying geometric information of the posterior distribution in order…
On Numerical Considerations for Riemannian Manifold Hamiltonian Monte Carlo
James A. Brofos, Roy R. Lederman
Riemannian manifold Hamiltonian Monte Carlo (RMHMC) is a sampling algorithm that seeks to adapt proposals to the local geometry of the posterior distribution. The specific form of…
Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals
James A. Brofos, Marylou Gabrié, Marcus A. Brubaker +1
Markov Chain Monte Carlo (MCMC) methods are a powerful tool for computation with complex probability distributions. However the performance of such methods is critically dependant…
Evaluating the Implicit Midpoint Integrator for Riemannian Manifold Hamiltonian Monte Carlo
James A. Brofos, Roy R. Lederman
Riemannian manifold Hamiltonian Monte Carlo is traditionally carried out using the generalized leapfrog integrator. However, this integrator is not the only choice and other integr…