25 citations · 35 across the 10 of their papers we have counts for
4 papers · 1 filter
Hessian-informed, Coordinate Friendly Hamiltonian Monte Carlo in Linear Time
Son Luu, Nikola Surjanovic, Zuheng Xu +2
Riemannian Hamiltonian Monte Carlo (RHMC) is a promising MCMC methodology thanks to its ability to accommodate position-dependent preconditioning and multi-step proposals. While RH…
Asymptotically exact variational flows via involutive MCMC kernels
Zuheng Xu, Trevor Campbell
Most expressive variational families -- such as normalizing flows -- lack practical convergence guarantees, as their theoretical assurances typically hold only at the intractable g…
Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs?
Son Luu, Zuheng Xu, Nikola Surjanovic +3
The Hamiltonian Monte Carlo (HMC) algorithm is often lauded for its ability to effectively sample from high-dimensional distributions. In this paper we challenge the presumed domin…
The computational asymptotics of Gaussian variational inference and the Laplace approximation
Zuheng Xu, Trevor Campbell
Gaussian variational inference and the Laplace approximation are popular alternatives to Markov chain Monte Carlo that formulate Bayesian posterior inference as an optimization pro…