… (also called Hybrid Monte Carlo) (HMC) involves a tradeoff between computational cost
and … a randomized version of the Hamiltonian Monte Carlo (also called Hybrid Monte Carlo) …

… The bouncy particle sampler is a Markov chain Monte Carlo method based on a … velocity
converges weakly towards a randomized Hamiltonian Monte Carlo (RHMC) process as the …

… Riemannian Hamiltonian Monte Carlo methods in the continuous time setting. We provide
a first result to establish invariance of a continuous time Riemannian Hamiltonian Monte Carlo …

… walk behavior in HMC algorithm is the randomization of momentum vector p init at the …
An α value of 0 is associated with the case of starting a new trajectory by total randomization …

… We consider randomized algorithms for simulating the evolution of a Hamiltonian \(H ={ \sum
\… First we provide a scheme to bound the error of the final quantum state in a randomized …

… randomized Hamiltonian Monte Carlo is introduced, as a robust, easy to use and computationally
fast alternative to conventional Markov chain Monte Carlo … generalizing Randomized …

… It is readily checked that μ is invariant for both the randomization and Hamiltonian steps. We
call (Xk,Vk)k∈N the idealized Hamiltonian Monte Carlo (HMC) chain. HMC is a widely used …

… sampler Mix & Match Hamiltonian Monte Carlo (MMHMC). The … We notice that randomization
of a step size commonly … On the one hand, randomization of a step size implies that a …

… Our implementation of HMC exploits (i) long and randomized integration times, and (ii) an
“algorithmic” warm start obtained by first running the unadjusted HMC chain. This surpasses …

… Here we propose an efficient and scalable computational technique for a state-of-the-art
Markov chain Monte Carlo methods, namely, Hamiltonian Monte Carlo. The key idea is to …