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Hamiltonian Monte Carlo algorithm

Unsupervised Post-Nonlinear Unmixing of Hyperspectral Images Using a Hamiltonian Monte Carlo Algorithm

Unsupervised Post-Nonlinear Unmixing of Hyperspectral Images Using a Hamiltonian Monte Carlo Algorithm

... Unsupervised Post-Nonlinear Unmixing of Hyperspectral Images Using a Hamiltonian Monte Carlo Algorithm Yoann Altmann, Member, IEEE, Nicolas Dobigeon, Senior Member, IEEE, and Jean-Yves T[r] ...

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A hamiltonian Monte Carlo method for non-smooth energy sampling

A hamiltonian Monte Carlo method for non-smooth energy sampling

... ns-HMC algorithm when the target energy function has a non-diifferentiable point (x = 0) that is reached with a non-zero ...ns-HMC algorithm is clearly converging faster than the rw-MH and ESS ...

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Improved polytope volume calculations based on Hamiltonian Monte Carlo with boundary reflections and sweet arithmetics

Improved polytope volume calculations based on Hamiltonian Monte Carlo with boundary reflections and sweet arithmetics

... studies Hamiltonian Monte Carlo (HMC) with reflections on the bound- ary of a domain, providing an enhanced alternative to Hit-and-run (HAR) to sample a target distribution restricted to the ...

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Monte Carlo algorithm for strongly interacting non-equilibrium quantum systems in nanoelectronics

Monte Carlo algorithm for strongly interacting non-equilibrium quantum systems in nanoelectronics

... on Monte Carlo ...Quantum Monte Carlo (QMC) already used in equilibrium in the Matsubara ...quenched Hamiltonian and tries to reach the steady ...

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Hamiltonian Monte Carlo with boundary reflections, and application to polytope volume calculations

Hamiltonian Monte Carlo with boundary reflections, and application to polytope volume calculations

... Second, in the particular case of polyhedral domains we present a robust implementation based on multi-precision arithmetic. This ingredient is mandatory to guarantee exact predicates and robust constructions, following ...

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Faster Hamiltonian Monte Carlo by Learning Leapfrog Scale

Faster Hamiltonian Monte Carlo by Learning Leapfrog Scale

... the algorithm theoretically benefits from a fast exploration of the pa- rameter space by accepting large transitions with high probability, this efficiency is marred by its high sensitivity to hand-tuned ...

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Monte Carlo Methods in Statistics

Monte Carlo Methods in Statistics

... and Hamiltonian or hybrid alternatives (Duane et ...Metropolis–Hastings algorithm whose scale is calibrated towards an acceptance rate of ...generic algorithm applying to any target (instead of a ...

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A hamiltonian Monte Carlo method for non-smooth energy sampling

A hamiltonian Monte Carlo method for non-smooth energy sampling

... rw-MH algorithm, and for the sake of comparison with other existing algorithms that are adapted to the multidimensional case, the KL divergence curves are also provided for the elliptical slice sampling (ESS) [10] ...

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Addressing nonlinearities in Monte Carlo

Addressing nonlinearities in Monte Carlo

... the Monte Carlo Method is no longer restricted to linear ...the Monte Carlo method and specialists of the physical prob- lem under ...standard Monte Carlo Method, according to ...

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Optimized Population Monte Carlo

Optimized Population Monte Carlo

... GAPIS algorithm [18] is an AIS method that exploits the gradient and the Hessian of the logarithm of the target, and also introduces an artificial repulsion among proposals to promote the diversity (without any ...

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Contributions to Monte Carlo Search

Contributions to Monte Carlo Search

... Nested Monte-Carlo (NMC) search algorithm. The former algorithm is directly related to our sampling strategy, while the latter is relevant since it has recently been applied with success to ...

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Méthodes de Monte Carlo en Vision Stéréoscopique

Méthodes de Monte Carlo en Vision Stéréoscopique

... MCMC estimation Fig. 4.9 – Evolution au cours du temps d’int´ egration de l’estimation de h τ (les 50 000 premi` eres it´ erations sont repr´ esent´ ees) de h τ , en fonction du nombre l de simulations cons´ ecutives ...

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Parallel Nested Monte-Carlo search

Parallel Nested Monte-Carlo search

... IV. Parallel algorithms In order to parallelize nested rollouts we define four types of processes: the root process, the median node processes, the dispatcher process and the client processes. These pro- cesses work at ...

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Pépite | Méthodes quasi-Monte Carlo et Monte Carlo : application aux calculs des estimateurs Lasso et Lasso bayésien

Pépite | Méthodes quasi-Monte Carlo et Monte Carlo : application aux calculs des estimateurs Lasso et Lasso bayésien

... algorithms around LASSO estimator In this chapter we study, as the temperature goes to zero, the oscilla- tion of a family of Gibbs measures around LASSO estimator. We derive new criteria for estimating LASSO, choosing ...

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Calcul d’Intégral par la Méthode de Monte-Carlo

Calcul d’Intégral par la Méthode de Monte-Carlo

... de Monte-Carlo pour calculer d’intégral par l’espérance dans le cas simple (unidimensionnelle) et compliquée (multidimensionnelles), de plus pour estimer l’erreur numérique de cette méthode on étudie la ...

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Monte Carlo method and sensitivity estimations

Monte Carlo method and sensitivity estimations

... most Monte Carlo algorithms, provided that they are based on an underlying multiple integral formulation, even if this formulation is not ...the Monte Carlo weight and take the ...the ...

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Quelques contributions sur les méthodes de Monte Carlo

Quelques contributions sur les méthodes de Monte Carlo

... Dans notre deuxième essai nous proposons plusieurs méthodes de réduction de variance pour l’algorithme de Metropolis Indépendant.. Avant une description plus détaillée du contenu des ess[r] ...

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Monte-Carlo and Domain-Deformation Sensitivities

Monte-Carlo and Domain-Deformation Sensitivities

... function. Monte-Carlo methods are preferred for complex geometry process simulations where radiative transfer is preponderant ...the Monte-Carlo method is used because of its ability to ...

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Étude des artefacts en tomodensitométrie par simulation Monte Carlo

Étude des artefacts en tomodensitométrie par simulation Monte Carlo

... CHAPITRE 2 INTERACTIONS DES PHOTONS AVEC LA MATIÈRE En imagerie médicale, on peut utiliser une source de rayons X ou de rayons gamma pour produire des images. La variation des tons de gris sur ces images dépend de la ...

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Line-sampling-based Monte Carlo method

Line-sampling-based Monte Carlo method

... E-mail: mathieu.galtier@insa-lyon.fr Null-collision Monte Carlo algorithms [1, 2, 3, 4] consist in adding a virtual null-collision coefficient to the real extinction one. These collisions, corresponding to ...

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