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Normalizing flows have shown great promise for modelling flexible probability distributions in a computationally tractable way. However, whilst data is often naturally described on Riemannian manifolds such as spheres, torii, and hyperbolic…

Machine Learning · Statistics 2020-12-10 Emile Mathieu , Maximilian Nickel

We demonstrate several techniques to encourage practical uses of neural networks for fluid flow estimation. In the present paper, three perspectives which are remaining challenges for applications of machine learning to fluid dynamics are…

Fluid Dynamics · Physics 2022-05-19 Masaki Morimoto , Kai Fukami , Kai Zhang , Koji Fukagata

We adapt the Gradient Discretisation Method (GDM), originally designed for elliptic and parabolic partial differential equations, to the case of a linear scalar hyperbolic equations. This enables the simultaneous design and convergence…

Numerical Analysis · Mathematics 2019-10-28 Jérôme Droniou , Robert Eymard , T. Gallouët , R. Herbin

Molecular dynamics (MD) and continuum simulations are carried out to investigate the influence of shear rate and surface roughness on slip flow of a Newtonian fluid. For weak wall-fluid interaction energy, the nonlinear shear-rate…

Soft Condensed Matter · Physics 2010-01-25 Anoosheh Niavarani , Nikolai V. Priezjev

Generating high-quality time-series data is challenging because real-world signals often exhibit multimodal patterns and multiscale dynamics, including oscillations and high-frequency variations. Flow Matching (FM) offers an efficient…

Machine Learning · Computer Science 2026-05-29 Junru Zhang , Lang Feng , Jinbo Wang , Xu Guo , Yucheng Wang , Han Yu , Min Wu , Yabo Dong , Duanqing Xu

In this paper we investigate a kind of generalized Ricci flow which possesses a gradient form. We study the monotonicity of the given function under the generalized Ricci flow and prove that the related system of partial differential…

Differential Geometry · Mathematics 2011-07-19 Chun-lei He , Sen Hu , De-Xing Kong , Kefeng Liu

We propose a visual SLAM method by predicting and updating line flows that represent sequential 2D projections of 3D line segments. While feature-based SLAM methods have achieved excellent results, they still face problems in challenging…

Computer Vision and Pattern Recognition · Computer Science 2021-03-18 Qiuyuan Wang , Zike Yan , Junqiu Wang , Fei Xue , Wei Ma , Hongbin Zha

In centralized settings, it is well known that stochastic gradient descent (SGD) avoids saddle points and converges to local minima in nonconvex problems. However, similar guarantees are lacking for distributed first-order algorithms. The…

Optimization and Control · Mathematics 2022-03-07 Brian Swenson , Ryan Murray , H. Vincent Poor , Soummya Kar

In this paper, we develop a new Randomized Global Generalized Minimum Residual (RGlGMRES) algorithm for efficiently computing solutions to large scale linear systems with multiple right hand sides.The proposed method builds on a recently…

Numerical Analysis · Mathematics 2026-02-17 Achraf Badahmane , Xian-Ming GU

We present a new method for numerical hydrodynamics which uses a multidimensional generalisation of the Roe solver and operates on an unstructured triangular mesh. The main advantage over traditional methods based on Riemann solvers, which…

Instrumentation and Methods for Astrophysics · Physics 2017-06-28 Sijme-Jan Paardekooper

High order methods are often desired for the evolution of ordinary differential equations, in particular those arising from the semi-discretization of partial differential equations. In prior work in we investigated the interplay between…

Numerical Analysis · Mathematics 2019-12-10 Adi Ditkowski , Sigal Gottlieb , Zachary J. Grant

Modeling real-world distributions can often be challenging due to sample data that are subjected to perturbations, e.g., instrumentation errors, or added random noise. Since flow models are typically nonlinear algorithms, they amplify these…

Machine Learning · Computer Science 2022-10-11 Sameera Ramasinghe , Kasun Fernando , Salman Khan , Nick Barnes

In this work, we make two improvements on the staggered grid hydrodynamics (SGH) Lagrangian scheme for modeling 2-dimensional compressible multi-material flows on triangular mesh. The first improvement is the construction of a dynamic local…

Computational Physics · Physics 2017-07-10 Hai-bo Zhao , Bo Xiao , Jing-song Bai , Shu-chao Duan , Gang-hua Wang , Ming-xian Kan

A rectangular grid formed by liquid filaments on a partially wetting substrate evolves in a series of breakups leading to arrays of drops with different shapes distributed in a rather regular bidimensional pattern. Our study is focused on…

Fluid Dynamics · Physics 2017-10-25 Ingrith Cuellar , Pablo D. Ravazzoli , Javier A. Diez , Alejandro G. González

A finite element method for solving nonlinear differential equations on a grid, with potential applicability to computational fluid dynamics (CFD), is developed and tested. The current method facilitates the computation of solutions of a…

Computational Physics · Physics 2014-09-04 Jesper Tveit

We consider shear-driven longitudinal flow of an exterior fluid over a periodic array of rectangular grooves filled with an immiscible interior fluid (the "lubricant"), the grooves being formed by infinitely thin ridges protruding from a…

Fluid Dynamics · Physics 2026-01-16 Gunnar G. Peng , Ehud Yariv , Ory Schnitzer

A new method for solving relativistic ideal hydrodynamics in (1+3)D is developed. Longitudinal and transverse radial flows are explicitly embedded and the hydrodynamic equations are reduced to a single equation for the transverse velocity…

Nuclear Theory · Physics 2009-11-06 Jinfeng Liao , Volker Koch

The proposed two-dimensional geometrically exact beam element extends our previous work by including the effects of shear distortion, and also of distributed forces and moments acting along the beam. The general flexibility-based…

Numerical Analysis · Mathematics 2025-08-06 Milan Jirasek , Martin Horak , Emma La Malfa Ribolla , Chiara Bonvissuto

The goal of my lecture is to present the introduction into the hydrodynamical version of the Grad-Shafranov equation. Although not so well-known as the full MHD one, it allows us to clarify the nontrivial structure of the Grad-Shafranov…

Astrophysics · Physics 2007-05-23 V. S. Beskin

Existing computationally efficient methods for penalized likelihood GAM fitting employ iterative smoothness selection on working linear models (or working mixed models). Such schemes fail to converge for a non-negligible proportion of…

Methodology · Statistics 2015-11-13 Simon N. Wood
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