相关论文: The Bjorken sum rule with Monte Carlo and Neural N…

Sequential Monte Carlo methods, also known as particle methods, are a popular set of techniques for approximating high-dimensional probability distributions and their normalizing constants. These methods have found numerous applications in…

This paper investigates a novel a-posteriori variance reduction approach in Monte Carlo image synthesis. Unlike most established methods based on lateral filtering in the image space, our proposition is to produce the best possible estimate…

In the following article we provide an exposition of exact computational methods to perform parameter inference from partially observed network models. In particular, we consider the duplication attachment (DA) model which has a likelihood…

Models with intractable normalizing functions have numerous applications. Because the normalizing constants are functions of the parameters of interest, standard Markov chain Monte Carlo cannot be used for Bayesian inference for these…

We discuss the use of a recent class of sequential Monte Carlo methods for solving inverse problems characterized by a semi-linear structure, i.e. where the data depend linearly on a subset of variables and nonlinearly on the remaining…

Using a simple picture of the constituent quark as a composite system of point-like partons, we construct the polarized parton distributions by a convolution between constituent quark momentum distributions and constituent quark structure…

These lectures introduce the non-specialist to the evaluation of spin structure functions from asymmetries measured in polarized deep-inelastic scattering experiments. The various steps leading from apparatus dependent counting rate…

Nucleon structure functions are studied within the chiral soliton approach to the bosonized Nambu-Jona-Lasinio model. The valence quark approximation is employed which is justified for moderate constituent quark masses ($\sim$ 400 MeV) as…

Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. These models extend spatially the static stability models adopted in geotechnical engineering, and…

This paper presents a novel stochastic framework to quantify the knock down in strength from out-of-plane wrinkles at the coupon level. The key innovation is a Markov Chain Monte Carlo algorithm which rigorously derives the stochastic…

We study polarized-spin structure functions of the nucleon within the bosonized Nambu-Jona-Lasinio model where the nucleon emerges as a chiral soliton. We present the electromagnetic polarized structure functions, $g_{1}(x)$ and $g_{2}(x)$…

Global analysis has been performed within the next-to-leading order in Quantum Chromodynamics (QCD) to determine polarized parton distributions with new experimental data in spin asymmetries. The new data set includes JLab, HERMES, and…

We introduce a Monte Carlo algorithm to efficiently compute transport properties of chaotic dynamical systems. Our method exploits the importance sampling technique that favors trajectories in the tail of the distribution of displacements,…

We present a consensus Monte Carlo algorithm that scales existing Bayesian nonparametric models for clustering and feature allocation to big data. The algorithm is valid for any prior on random subsets such as partitions and latent feature…

Starting from Martin, Roberts and Stirling fit for unpolarized deep inelastic structure functions and using the newest experimental data on spin asymmetries we get a fit which provides polarized quark distributions. We analyze the behaviour…

We investigate structure functions in deep inelastic scattering processes (DIS) at Bj\"{o}rken limit and found that they are factorized into the longitudinal and transversal parts. We see that the longitudinal part can be linked to exact…

In many models used in engineering and science, material properties are uncertain or spatially varying. For example, in geophysics, and porous media flow in particular, the uncertain permeability of the material is modelled as a random…

By the method of Poissonization we confirm some existing results concerning consistent estimation of the structural distribution function in the situation of a large number of rare events. Inconsistency of the so called natural estimator is…

We briefly review the use of the order parameter probability distribution function as a useful tool to obtain the critical properties of statistical mechanical models using computer Monte Carlo simulations. Some simple discrete spin…

We discuss the present situation with regard to polarised nucleon structure function measurements. In particular we examine the status of the Bjorken sum rule in the light of the recent data on the spin structure functions of (i) the…