We study Hamiltonian Monte Carlo (HMC) samplers based on splitting the Hamiltonian H as H0(θ,p)+U1(θ), where H0 is quadratic and U1 small. We show that, in general, such samplers suffer from stepsize stability restrictions similar to those of algorithms based on the standard leapfrog integrator. The restrictions may be circumvented by preconditioning the dynamics. Numerical experiments show that, when the H0(θ,p)+U1(θ) splitting is combined with preconditioning, it is possible to construct samplers far more efficient than standard leapfrog HMC.This work has been supported by Ministerio de Ciencia e Innovación (Spain) through project PID2019-104927GB-C21, MCIN/AEI/10.13039/501100011033, ERDF ("A way of making Europe")
The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computat...
The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computat...
This paper surveys in detail the relations between numerical integration and the Hamiltonian (or hyb...
We study Hamiltonian Monte Carlo (HMC) samplers based on splitting the Hamiltonian H as H0(θ,p)+U1(θ...
We construct integrators to be used in Hamiltonian (or Hybrid) Monte Carlo sampling. The new integra...
Splitting schemes are numerical integrators for Hamiltonian problems that may advantageously replace...
[EN] We construct integrators to be used in Hamiltonian (or Hybrid) Monte Carlo sampling. The new in...
Modified Hamiltonian Monte Carlo (MHMC) methods combine the ideas behind two popular sampling approa...
We show how the Hamiltonian Monte Carlo algorithm can sometimes be speeded up by “splitting ” the Ha...
We propose a splitting Hamiltonian Monte Carlo (SHMC) algorithm, which can be computationally effici...
We construct numerical integrators for Hamiltonian problems that may advantageously replace the stan...
We report on what seems to be an intriguing connection between variable integration time and partial...
Hamiltonian Monte Carlo (HMC) samples efficiently from high-dimensional posterior distributions with...
The modified Hamiltonian Monte Carlo (MHMC) methods, i.e., importance sampling methods that use modi...
154 p.The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in co...
The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computat...
The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computat...
This paper surveys in detail the relations between numerical integration and the Hamiltonian (or hyb...
We study Hamiltonian Monte Carlo (HMC) samplers based on splitting the Hamiltonian H as H0(θ,p)+U1(θ...
We construct integrators to be used in Hamiltonian (or Hybrid) Monte Carlo sampling. The new integra...
Splitting schemes are numerical integrators for Hamiltonian problems that may advantageously replace...
[EN] We construct integrators to be used in Hamiltonian (or Hybrid) Monte Carlo sampling. The new in...
Modified Hamiltonian Monte Carlo (MHMC) methods combine the ideas behind two popular sampling approa...
We show how the Hamiltonian Monte Carlo algorithm can sometimes be speeded up by “splitting ” the Ha...
We propose a splitting Hamiltonian Monte Carlo (SHMC) algorithm, which can be computationally effici...
We construct numerical integrators for Hamiltonian problems that may advantageously replace the stan...
We report on what seems to be an intriguing connection between variable integration time and partial...
Hamiltonian Monte Carlo (HMC) samples efficiently from high-dimensional posterior distributions with...
The modified Hamiltonian Monte Carlo (MHMC) methods, i.e., importance sampling methods that use modi...
154 p.The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in co...
The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computat...
The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computat...
This paper surveys in detail the relations between numerical integration and the Hamiltonian (or hyb...