Apr 27, 2020 · We derive a novel adjoint method that propagates the minimal information needed to construct the gradient of the approximate marginal likelihood.
Sep 4, 2016 · We proposed a Hamiltonian Monte Carlo (HMC) method with Laplace kinetic energy, and demonstrate the connection between slice sampling and ...
Sep 19, 2016 · We proposed a Hamiltonian Monte Carlo HMC method with Laplace kinetic energy, and demonstrate the connection between slice sampling and ...
We proposed a Hamiltonian Monte Carlo (HMC) method with Laplace kinetic energy, and demonstrate the connection between slice sampling and proposed HMC ...
Jun 10, 2020 · We derive a novel adjoint method that propagates the minimal information needed to construct the gradient of the approximate marginal likelihood.
Dec 27, 2023 · We show that Hamiltonian Monte Carlo, applied to the von Mises distribution with Laplace distribution for the momentum, has exactly solvable ...
Mar 7, 2020 · In this article we present an extension that can efficiently explore target distributions with discontinuous densities.
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Laplacian Hamiltonian Monte Carlo. Published in ECML, 2016. Recommended citation: Yizhe Zhang, Changyou Chen, Ricardo Henao, Lawrence Carin https://dl.acm.org ...
Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo (MCMC) method that uses the derivatives of the density function being sampled to generate efficient ...
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Aug 23, 2024 · We show that Hamiltonian Monte Carlo with Laplacian momentum has exactly solvable equations of motion and, with an appropriate travel time ...