Oct 21, 2021 · We present a novel convergence analysis for HMC utilizing new analytic and probabilistic arguments. The convergence is rigorously established ...
In our framework, we show that plain HMC with asymmetrical momentum distributions breaks a key self-adjointness requirement. We propose a modified version that ...
Existing rigorous convergence guarantees for the Hamiltonian Monte Carlo(HMC) algorithm use Gaussian auxiliary momentum variables, ...
Nov 20, 2017 · The negation of the momentum variables at the end of the trajectory makes the Metropolis proposal symmetrical, as needed for the acceptance probability above ...
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Dec 23, 2021 · Both methods use a standard normal distribution for the momentum distribution and the proposal distribution, respectively. I show the ...
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Feb 11, 2023 · In order to implement the MHGJ algorithm, one requires choosing an appropriate distribution S and the deterministic map, g. Hamiltonian Monte ...
Hamiltonian Monte-Carlo (HMC) method is an approach to construct an invariant distribution other than generation of Markov chain.
Hamiltonian Monte Carlo provides an elegant mecha- nism to do this by simulating a particle moving along the contour lines of a dynamical system, constructed ...
The Hamiltonian Monte Carlo (HMC) is a new MCMC approach that has been shown to work better than the usual MH algorithm.
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What is Hamiltonian Monte Carlo?
What is the acceptance rate for Hamiltonian Monte Carlo?
The Hamiltonian Monte Carlo algorithm (originally known as hybrid Monte Carlo) is a Markov chain Monte Carlo method for obtaining a sequence of random samples
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