Zobrazeno 1 - 10
of 82 847
pro vyhledávání: '"HMC"'
Autor:
Lundstrum, Erik
I describe a generalization of the Hybrid Monte Carlo (HMC) algorithm in which the molecular dynamics (MD) steps utilize Nambu generalized Hamiltonian dynamics. Characterized by multiple Hamiltonian functions, this formalism allows me to include forc
Externí odkaz:
http://arxiv.org/abs/2409.18958
Neural Surrogate HMC: Accelerated Hamiltonian Monte Carlo with a Neural Network Surrogate Likelihood
Bayesian Inference with Markov Chain Monte Carlo requires efficient computation of the likelihood function. In some scientific applications, the likelihood must be computed by numerically solving a partial differential equation, which can be prohibit
Externí odkaz:
http://arxiv.org/abs/2407.20432
Diffusion generative models have excelled at diverse image generation and reconstruction tasks across fields. A less explored avenue is their application to discriminative tasks involving regression or classification problems. The cornerstone of mode
Externí odkaz:
http://arxiv.org/abs/2405.05255
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Osborn, James C.
Publikováno v:
PoS(LATTICE2023)023
We investigate the effectiveness of tuning HMC parameters using information from the gradients of the HMC acceptance probability with respect to the parameters. In particular, the optimization of the trajectory length and parameters for higher order
Externí odkaz:
http://arxiv.org/abs/2402.04976
Autor:
Jung, Chulwoo, Christ, Norman H.
We report on our study of the Riemannian Manifold HMC (RMHMC) algorithm with the mass term for the gauge momenta replaced by rational functions of the gauge covariant Laplace operator. A comparison of HMC and RMHMC on a 2+1+1 flavor dynamical ensembl
Externí odkaz:
http://arxiv.org/abs/2401.13226
Autor:
Fukuma, Masafumi
The Worldvolume Hybrid Monte Carlo method (WV-HMC method) [arXiv:2012.08468] is a reliable and versatile algorithm towards solving the sign problem. Similarly to the tempered Lefschetz thimble method, this method removes the ergodicity problem inhere
Externí odkaz:
http://arxiv.org/abs/2311.10663
Autor:
Tran, Jimmy Huy, Kleppe, Tore Selland
Three approaches for adaptively tuning diagonal scale matrices for HMC are discussed and compared. The common practice of scaling according to estimated marginal standard deviations is taken as a benchmark. Scaling according to the mean log-target gr
Externí odkaz:
http://arxiv.org/abs/2403.07495
To accelerate the HMC with field transformation, we consider a variant of the trivializing map, the decimation map, which can be regarded as a coarse-graining transformation. Using the 2D $U(1)$ pure gauge model, combined with the guided Monte Carlo
Externí odkaz:
http://arxiv.org/abs/2312.04800
Bayesian inference with deep generative prior has received considerable interest for solving imaging inverse problems in many scientific and engineering fields. The selection of the prior distribution is learned from, and therefore an important repre
Externí odkaz:
http://arxiv.org/abs/2310.17817