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The recently developed semi-parametric generalized linear model (SPGLM) offers more flexibility as compared to the classical GLM by including the baseline or reference distribution of the response as an additional parameter in the model.…

Methodology · Statistics 2024-04-09 Entejar Alam , Peter Müller , Paul J. Rathouz

We propose a multiple relaxation time Boltzmann equation collision model by systematically assigning a separate relaxation time to each of the central moments of the distribution function. The Chapman-Enskog calculation leads to correct…

Computational Physics · Physics 2020-10-06 Xiaowen Shan

Lattice Boltzmann methods are usually derived under the assumption of isotropy. In this work, we present a derivation of a Lattice Boltzmann method for anisotropic fluid flow. Starting from an anisotropic equilibrium distribution, we show a…

Fluid Dynamics · Physics 2026-05-27 Benjamin Kellers , Julius Weinmiller , Arnulf Latz , Timo Danner

Thermal fluctuations play a central role in fluid dynamics at mesoscopic scales and must be incorporated into numerical schemes in a manner consistent with statistical mechanics. In this work, we develop a fluctuating lattice Boltzmann…

Fluid Dynamics · Physics 2026-02-19 Alessandro De Rosis , Yang Zhou

A framework of finite-velocity model based Boltzmann equation has been developed for convection-diffusion equations. These velocities are kept flexible and adjusted to control numerical diffusion. A flux difference splitting based kinetic…

Numerical Analysis · Mathematics 2024-10-01 S. V. Raghurama Rao , K. S. Shrinath , Ankit Ruhi , Veeredhi Vasudeva Rao

Computational methods for learning to sample from the Boltzmann distribution -- where the target distribution is known only up to an unnormalized energy function -- have advanced significantly recently. Due to the lack of explicit target…

Machine Learning · Statistics 2025-11-26 Guan-Horng Liu , Jaemoo Choi , Yongxin Chen , Benjamin Kurt Miller , Ricky T. Q. Chen

A novel Lattice Boltzmann method is derived using the Principle of Minimum Cross Entropy (MinxEnt) via the minimization of Kullback-Leibler Divergence (KLD). By carrying out the actual single step Newton-Raphson minimization (MinxEnt-LBM) a…

Computational Physics · Physics 2018-01-12 Tyler L Wilson , Mary Pugh , Francis Dawson

We examine the applicability of diffusive lattice Boltzmann methods to simulate the fluid transport through barrier coatings, finding excellent agreement between simulations and analytical predictions for standard parameter choices. To…

Computational Physics · Physics 2017-06-28 Kyle T. Strand , Aaron J. Feickert , Alexander J. Wagner

We present a regularized version of the color gradient lattice Boltzmann (LB) scheme for the simulation of droplet formation in microfluidic devices of experimental relevance. The regularized version is shown to provide computationally…

The Plateau-Rayleigh instability causes the fragmentation of a liquid ligament into smaller droplets. In this study a numerical study of this phenomenon based on a single relaxation time (SRT) pseudo-potential lattice Boltzmann method (LBM)…

Computational Physics · Physics 2019-04-29 Daniele Chiappini , Xiao Xue , Giacomo Falcucci , Mauro Sbragaglia

Exploring the free-energy landscape along reaction coordinates or system parameters $\lambda$ is central to many studies of high-dimensional model systems in physics, e.g. large molecules or spin glasses. In simulations this usually…

Statistical Mechanics · Physics 2018-09-05 Viveca Lindahl , Jack Lidmar , Berk Hess

This paper introduces and analyses interacting underdamped Langevin algorithms, termed Kinetic Interacting Particle Langevin Monte Carlo (KIPLMC) methods, for statistical inference in latent variable models. We propose a diffusion process…

Computation · Statistics 2026-04-17 Paul Felix Valsecchi Oliva , O. Deniz Akyildiz

The influence of the use of the generalized Hermite polynomial on the Hermite-based lattice Boltzmann (LB) construction approach, lattice sets, the thermal weights, moments and the equilibrium distribution function (EDF) are addressed. A…

Computational Engineering, Finance, and Science · Computer Science 2013-04-22 Raúl Machado

In this paper, we introduce a novel Distributed Markov Chain Monte Carlo (MCMC) inference method for the Bayesian Non-Parametric Latent Block Model (DisNPLBM), employing the Master/Worker architecture. Our non-parametric co-clustering…

Machine Learning · Statistics 2024-02-05 Reda Khoufache , Anisse Belhadj , Hanene Azzag , Mustapha Lebbah

Efficient sampling of complex data distributions can be achieved using trained invertible flows (IF), where the model distribution is generated by pushing a simple base distribution through multiple non-linear bijective transformations.…

Machine Learning · Computer Science 2021-07-13 Daniel O'Connor , Walter Vinci

This paper aims to conduct a comprehensive theoretical analysis of current diffusion models. We introduce a novel generative learning methodology utilizing the Schr{\"o}dinger bridge diffusion model in latent space as the framework for…

Machine Learning · Statistics 2024-12-24 Yuling Jiao , Lican Kang , Huazhen Lin , Jin Liu , Heng Zuo

This paper is concerned with the large deviation principle of the stochastic reaction-diffusion lattice systems defined on the N-dimensional integer set, where the nonlinear drift term is locally Lipschitz continuous with polynomial growth…

Dynamical Systems · Mathematics 2023-05-12 Bixiang Wang

Stochastic sampling algorithms such as Langevin Monte Carlo are inspired by physical systems in a heat bath. Their equilibrium distribution is the canonical ensemble given by a prescribed target distribution, so they must balance…

High Energy Physics - Lattice · Physics 2025-05-06 Jakob Robnik , Uroš Seljak

In this study a new numerical approach of the fluid dynamic, the lattice Boltzmann method (LBM), is used to solved the stream in a atmospheric Argon-nitrogen plasma jet. The axial symmetry and the variation of density, viscosity and…

Materials Science · Physics 2010-02-17 Ridha Djebeli , Nicolas Calve , Bernard Pateyron , Mohamed El Ganaoui , Habib Sammouda

Solution of the discretized Lippmann-Schwinger equation in the spatial frequency domain involves the inversion of a linear operator specified by the scattering potential. To regularize this inevitably ill-conditioned problem, we propose a…

Computational Physics · Physics 2020-10-30 Subeen Pang , George Barbastathis
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