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Research map / Probabilistic and scientific modeling / Variational and generative sampling

Magnetic Hamiltonian Monte Carlo

ICML 2017 · Probabilistic and scientific modeling › Variational and generative sampling · approach: Stochastic gradient MCMC · 22 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add magnetic dynamics coupling large- and small-variance directionsHMC · 2D ill-conditioned Gaussianabsolute bias x1^2: .947 -> .657Helped
Add magnetic dynamics coupling large- and small-variance directionsHMC · 2D ill-conditioned Gaussianabsolute bias x2^2: .00108 -> .000280Helped
Add magnetic dynamics coupling large- and small-variance directionsHMC · 10D ill-conditioned Gaussianabsolute bias x1^2: 24.7 -> 9.68Helped
Add magnetic dynamics coupling large- and small-variance directionsHMC · 10D ill-conditioned Gaussianabsolute bias x10^2: 0.00376 -> 0.00127Helped
Add magnetic field with g=0.1HMC · 2D Gaussian mixturebias x: .0132 -> .00239Helped
Add magnetic field with g=0.1HMC · 2D Gaussian mixturebias x^2: 0.00264 -> 0.000596Helped
Add magnetic perturbation in the ab planeHMC · FitzHugh-Nagumo posteriorESS(b)/time (s): 1.33 -> 1.47Helped
Add magnetic perturbation in the ab planeHMC · FitzHugh-Nagumo posteriorESS(c)/time (s): 2.55 -> 2.77Helped
Add magnetic perturbation in the ac planeHMC · FitzHugh-Nagumo posteriorESS(b)/time (s): 1.33 -> 1.42Helped
Add magnetic perturbation in the ac planeHMC · FitzHugh-Nagumo posteriorESS(c)/time (s): 2.55 -> 2.64Helped
Add magnetic perturbation in the bc planeHMC · FitzHugh-Nagumo posteriorESS(b)/time (s): 1.33 -> 1.37Helped
Add magnetic perturbation in the bc planeHMC · FitzHugh-Nagumo posteriorESS(c)/time (s): 2.55 -> 2.73Helped

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