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The Earth movers distance (EMD) is a measure of distance between probability distributions which is at the heart of mass transportation theory. Recent research has shown that the EMD plays a crucial role in studying the potential impact of…

Computation · Statistics 2013-10-15 Kyle Treleaven , Emilio Frazzoli

We study a paradigmatic system with long-range interactions: the Hamiltonian Mean-Field Model (HMF). It is shown that in the thermodynamic limit this model does not relax to the usual equilibrium Maxwell-Boltzmann distribution. Instead, the…

Statistical Mechanics · Physics 2011-07-08 Renato Pakter , Yan Levin

Heat radiation and near-field radiative heat transfer can be strongly manipulated by adjusting geometrical shapes, optical properties, or the relative positions of the objects involved. Typically these objects are considered as embedded in…

Classical Physics · Physics 2017-02-15 Boris Müller , Roberta Incardone , Mauro Antezza , Thorsten Emig , Matthias Krüger

This paper presents a multiscale modeling framework (MMF) to model moist atmospheric limited-area weather. The MMF resolves large-scale convection using a coarse grid while simultaneously resolving local features through numerous fine local…

Numerical Analysis · Mathematics 2024-07-09 Soonpil Kang , James F. Kelly , Anthony P. Austin , Francis X. Giraldo

The paper deals with the homogenization of deformable porous media saturated by two-component electrolytes. The model relevant to the microscopic scale describes steady states of the medium while reflecting essential physical phenomena,…

Computational Physics · Physics 2019-01-25 Jana Turjanicová , Eduard Rohan , Vladimír Lukeš

The density-matrix renormalization group (DMRG) applied to transfer matrices allows it to calculate static as well as dynamical properties of one-dimensional quantum systems at finite temperature in the thermodynamic limit. To this end the…

Strongly Correlated Electrons · Physics 2007-12-20 S. Glocke , A. Klümper , J. Sirker

Generalized linear mixed models (GLMM) are used for inference and prediction in a wide range of different applications providing a powerful scientific tool. An increasing number of sources of data are becoming available, introducing a…

Computation · Statistics 2019-03-19 Aliaksandr Hubin , Geir Storvik

Charge transport processes in disordered complex media are accompanied by anomalously slow relaxation for which usually a broad distribution of relaxation times is adopted. To account for those properties of the environment, a standard…

Statistical Mechanics · Physics 2009-11-10 Ewa Gudowska-Nowak , Kinga Bochenek , Agnieszka Jurlewicz , Karina Weron

In this paper, we propose GOHOME, a method leveraging graph representations of the High Definition Map and sparse projections to generate a heatmap output representing the future position probability distribution for a given agent in a…

Computer Vision and Pattern Recognition · Computer Science 2021-09-22 Thomas Gilles , Stefano Sabatini , Dzmitry Tsishkou , Bogdan Stanciulescu , Fabien Moutarde

Traditional gradient-based sampling methods, like standard Hamiltonian Monte Carlo, require that the desired target distribution is continuous and differentiable. This limits the types of models one can define, although the presented models…

Computation · Statistics 2025-04-28 Jimmy Huy Tran , Tore Selland Kleppe

A fast inverse heat conduction model (IHCM) is developed for estimating unknown properties of multi-layer composites considering internal heat generation. This work builds on the validated analytical forward models presented in Part I.…

Applied Physics · Physics 2025-07-10 Gan Fu , Mitrofan Curti , Calina Ciuhu , Elena A. Lomonova

This work presents a hierarchical model for solute transport in bounded layered porous media with random permeability. The model generalizes the Taylor-Aris dispersion theory to stochastic transport in random layered porous media with a…

Fluid Dynamics · Physics 2018-07-27 Zhijie Xu , Alexandre M. Tartakovsky

We present and derive a novel double-continuum transport model based on pore-scale characteristics. Our approach relies on building a simplified unit cell made up of immobile and mobile continua. We employ a numerically resolved pore-scale…

Fluid Dynamics · Physics 2019-06-26 Giulia Ceriotti , Anna Russian , Diogo Bolster , Giovanni Porta

Despite the widespread utilization of Gaussian process models for versatile nonparametric modeling, they exhibit limitations in effectively capturing abrupt changes in function smoothness and accommodating relationships with heteroscedastic…

Machine Learning · Statistics 2023-09-01 Taehee Lee , Jun S. Liu

We develop a generalized method of moments (GMM) approach for fast parameter estimation in a new class of Dirichlet latent variable models with mixed data types. Parameter estimation via GMM has been demonstrated to have computational and…

Statistics Theory · Mathematics 2016-03-24 Shiwen Zhao , Barbara E. Engelhardt , Sayan Mukherjee , David B. Dunson

In this work, we propose a generalized multiscale inversion algorithm for heterogeneous problems that aims at solving an inverse problem on a computational coarse grid. Previous inversion techniques for multiscale problems seek a…

Numerical Analysis · Mathematics 2017-07-27 Eric T. Chung , Yalchin Efendiev , Bangti Jin , Wing Tat Leung , Maria Vasilyeva

Generalized spatial modulation (GSM) is a spectral-efficient technique used in multiple-input multiple-output (MIMO) wireless communications when the number of radio frequency chains at the transmitter is less than the number of transmit…

Information Theory · Computer Science 2020-08-11 Lakshit Singla , Lakshmi Natarajan

We study heat transport in a one-dimensional chain of a finite number $N$ of identical cells, coupled at its boundaries to stochastic particle reservoirs. At the center of each cell, tracer particles collide with fixed scatterers,…

Statistical Mechanics · Physics 2022-04-10 Pierre Collet , Jean-Pierre Eckmann , Carlos Mejia-Monasterio

The flexible profile approach proposed earlier to create CTM (compact or reduced order thermal models) is extended to cover the area of conjugate heat transfer. The flexible profile approach is a methodology that allows building a highly…

General Physics · Physics 2008-01-08 M. -N. Sabry

Mean-field theories have proven to be efficient tools for exploring diverse phases of matter, complementing alternative methods that are more precise but also more computationally demanding. Conventional mean-field theories often fall short…

Strongly Correlated Electrons · Physics 2024-09-04 Junyi Zhang , Zhengqian Cheng
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