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Robust Bayesian inference using density power divergence (DPD) has emerged as a promising approach for handling outliers in statistical estimation. Although the DPD-based posterior offers theoretical guarantees of robustness, its practical…

Methodology · Statistics 2025-12-11 Naruki Sonobe , Tomotaka Momozaki , Tomoyuki Nakagawa

The algebraic properties of drift-flux two-phase fluids models without gravitational and wall friction forces are studied. More precisely, for the two fluids we consider equation of states of polytropic gases. We perform a classification…

Fluid Dynamics · Physics 2021-06-14 Andronikos Paliathanasis

We consider a discrete model of planar elasticity where the particles, in the reference configuration, sit on a regular triangular lattice and interact through nearest neighbor pairwise potentials, with bonds modeled as linearized elastic…

The discontinuous Galerkin (DG) method is an established method for computing approximate solutions of partial differential equations in many applications. Unlike continuous finite elements, in DG methods, numerical fluxes are used to…

Numerical Analysis · Mathematics 2019-12-02 Kenneth Duru , Leonhard Rannabauer , Alice-Agnes Gabriel , Heiner Igel

A numerical method for coupled 3D-1D problems with discontinuous solutions at the interfaces is derived and discussed. This extends a previous work on the subject where only continuous solutions were considered. Thanks to properly defined…

Numerical Analysis · Mathematics 2022-03-04 Stefano Berrone , Denise Grappein , Stefano Scialò

We present a field formulation for defects that draws from the classical representation of the cores as force dipoles. We write these dipoles as singular distributions. Exploiting the key insight that the variational setting is the only…

Materials Science · Physics 2016-06-02 Zhenlin Wang , Shiva Rudraraju , Krishna Garikipati

We present Deformable Voxel Grids (DVGs) for 3D shapes comparison and processing. It consists of a voxel grid which is deformed to approximate the silhouette of a shape, via energy-minimization. By interpreting the DVG as a local…

Computer Vision and Pattern Recognition · Computer Science 2022-11-22 Raphaël Groscot , Laurent D. Cohen

A general framework for performing event-driven simulations of systems with semi-flexible or rigid bodies interacting under impulsive torques and forces is outlined. Two different approaches are presented. In the first, the dynamics and…

Statistical Mechanics · Physics 2007-05-23 Lisandro Hernandez de la Pena , Ramses van Zon , Jeremy Schofield , Sheldon B. Opps

The first part of this article develops a variational formulation for relativistic mechanics. The results are established through standard tools of variational analysis and differential geometry. The novelty here is that the main motion…

General Mathematics · Mathematics 2020-03-30 Fabio Botelho

The existence of exponential dichotomies has been well-established as a powerful tool to study existence, stability, and bifurcations of coherent structures. Currently, the application of exponential dichotomies to elliptic problems posed…

Analysis of PDEs · Mathematics 2026-03-25 Margaret Beck , Ryan Goh , Alanna Haslam-Hyde

A state-of-the-art deep domain decomposition method (D3M) based on the variational principle is proposed for partial differential equations (PDEs). The solution of PDEs can be formulated as the solution of a constrained optimization…

Machine Learning · Computer Science 2020-04-03 Ke Li , Kejun Tang , Tianfan Wu , Qifeng Liao

A consistent treatment of the coupling of surface energy and elasticity within the multi-phase- field framework is presented. The model accurately reproduces stress distribution in a number of analytically tractable, yet non-trivial, cases…

Mesoscale and Nanoscale Physics · Physics 2018-01-17 Raphael Schiedung , Ingo Steinbach , Fathollah Varnik

In this paper a spectral-Lagrangian method for the Boltzmann equation for a multi-energy level gas is proposed. Internal energy levels are treated as separate species and inelastic collisions (leading to internal energy excitation and…

Numerical Analysis · Mathematics 2014-03-05 Alessandro Munafo , Jeffrey R. Haack , Irene M. Gamba , Thierry E. Magin

This paper develops a comprehensive mathematical framework for energy-based modeling of physical systems, with particular emphasis on preserving fundamental structural properties throughout the modeling and discretization process. The…

Numerical Analysis · Mathematics 2025-12-11 M. H. M Rashid

Understanding the decisions of tree-based ensembles and their relationships is pivotal for machine learning model interpretation. Recent attempts to mitigate the human-in-the-loop interpretation challenge have explored the extraction of the…

Machine Learning · Computer Science 2024-04-05 Leonardo Arrighi , Luca Pennella , Gabriel Marques Tavares , Sylvio Barbon Junior

Differentiable physics provides a new approach for modeling and understanding the physical systems by pairing the new technology of differentiable programming with classical numerical methods for physical simulation. We survey the rapidly…

Machine Learning · Computer Science 2021-09-17 Bharath Ramsundar , Dilip Krishnamurthy , Venkatasubramanian Viswanathan

The accurate, reliable and efficient numerical approximation of multi-physics processes in heterogeneous porous media with varying media coefficients that include fluid flow and structure interactions is of fundamental importance in energy,…

Numerical Analysis · Mathematics 2018-01-17 Uwe Köcher

In contrast to the traditional elastodynamic equations, a more comprehensive formulation of one dimensional (1D) elastodynamic equations is given for inhomogeneous media by using the coordinate transformation method. These modified…

Classical Physics · Physics 2018-03-23 Ruiwen Yao , Zhihai Xiang

The recently developed dynamic discretization discovery (DDD) is a powerful method that allows many time-dependent problems to become more tractable. While DDD has been applied to a variety of problems, one particular challenge has been to…

Discrete Mathematics · Computer Science 2023-03-03 Madison Van Dyk , Jochen Koenemann

We address the mechanics of an elastic ribbon subjected to twist and tensile load. Motivated by the classical work of Green and a recent experiment that discovered a plethora of morphological instabilities, we introduce a comprehensive…

Soft Condensed Matter · Physics 2014-08-18 Julien Chopin , Vincent Démery , Benny Davidovitch