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Giving explicit parametrizations of discrete constant Gaussian curvature surfaces of revolution that are defined from an integrable systems approach, we study Ricci flow for discrete surfaces, and see how discrete surfaces of revolution…

Differential Geometry · Mathematics 2023-12-14 Naoya Suda

Diffusion models have revolutionized generative tasks through high-fidelity outputs, yet flow matching (FM) offers faster inference and empirical performance gains. However, current foundation FM models are computationally prohibitive for…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Johannes Schusterbauer , Ming Gui , Frank Fundel , Björn Ommer

Energy distributions of high frequency linear wave fields are often modelled in terms of flow or transport equations with ray dynamics given by a Hamiltonian vector field in phase space. Applications arise in underwater and room acoustics,…

Computational Physics · Physics 2014-08-12 David Chappell , Gregor Tanner , Niels Sondergaard , Dominik Loechel

A new discretization approach is presented for the simulation of flow in complex poro-fractured media described by means of the Discrete Fracture and Matrix Model. The method is based on the numerical optimization of a properly defined…

Numerical Analysis · Mathematics 2020-04-10 Stefano Berrone , Alessandro D'Auria , Stefano Scialo'

The computation of electrical flows is a crucial primitive for many recently proposed optimization algorithms on weighted networks. While typically implemented as a centralized subroutine, the ability to perform this task in a fully…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-01 Luca Becchetti , Vincenzo Bonifaci , Emanuele Natale

We introduce a rapid and precise analytical approach for analyzing cerebral blood flow (CBF) using Diffuse Correlation Spectroscopy (DCS) with the application of the Extreme Learning Machine (ELM). Our evaluation of ELM and existing…

Machine Learning · Computer Science 2024-02-02 Xi Chen , Zhenya Zang , Xingda Li

Accurate and efficient prediction of multi-scale flows remains a formidable challenge. Constructing theoretical models and numerical methods often involves the design and optimization of parameters. While gradient descent methods have been…

Computational Physics · Physics 2026-02-10 Tianbai Xiao

Knowledge of the underlying mechanisms of multiphase flow dynamics in porous media is crucial for optimizing subsurface engineering applications like geological carbon sequestration. However, studying the micro-mechanisms of multiphase…

Fluid Dynamics · Physics 2025-08-01 Quanwei Dai , Kang Duan , Chung-Yee Kwok

We develop a compactness theory for super Ricci flows, which lays the foundations for the partial regularity theory in [Bam20b]. Our results imply that any sequence of super Ricci flows of the same dimension that is pointed in an…

Differential Geometry · Mathematics 2023-08-16 Richard H Bamler

We extend the Balancing Domain Decomposition by Constraints (BDDC) method to flows in porous media discretised by mixed-hybrid finite elements with combined mesh dimensions. Such discretisations appear when major geological fractures are…

Numerical Analysis · Mathematics 2015-11-24 Jakub Šístek , Jan Březina , Bedřich Sousedík

Continuous conformal transformation minimizes the conformal energy. The convergence of minimizing discrete conformal energy when the discrete mesh size tends to zero is an open problem. This paper addresses this problem via a careful error…

Numerical Analysis · Mathematics 2022-10-21 Zhenyue Zhang , Zhong-Heng Tan

We first proved a compactness theorem of the K\"ahler metrics, which confirms a prediction of Chen. Then we prove several eigenvalue estimates along the Calabi flow. Combining the compactness theorem and these eigenvalue estimates, we…

Differential Geometry · Mathematics 2014-12-31 Haozhao Li , Kai Zheng

We introduce Statistical Flow Matching (SFM), a novel and mathematically rigorous flow-matching framework on the manifold of parameterized probability measures inspired by the results from information geometry. We demonstrate the…

Machine Learning · Computer Science 2025-11-26 Chaoran Cheng , Jiahan Li , Jian Peng , Ge Liu

Flow-matching generative models are increasingly used to simulate cell responses to biological perturbations. However, the design space for building such models is large and underexplored. We systematically analyse the design space of flow…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Charles Jones , Emmanuel Noutahi , Jason Hartford , Cian Eastwood

The aim of this paper is to investigate the fractional combinatorial Calabi flow for hyperbolic bordered surfaces. By Lyapunov theory, it is proved that the flow exists for all time and converges exponentially to a conformal factor that…

Complex Variables · Mathematics 2025-07-15 Shengyu Li , Zhi-Gang Wang

In this paper we introduce and study a new kind of hyperbolic geometric flows --dissipative hyperbolic geometric flow. This kind of flow is defined by a system of quasilinear wave equations with dissipative terms. Some interesting exact…

Differential Geometry · Mathematics 2007-09-18 Wen-Rong Dai , De-Xing Kong , Kefeng Liu

Diffeomorphic matching (only one of several names for this technique) is a technique for non-rigid registration of curves and surfaces in which the curve or surface is embedded in the flow of a time-series of vector fields. One seeks the…

Numerical Analysis · Mathematics 2009-11-13 C. J. Cotter

The 2D Ricci flow equation in the conformal gauge is studied using the linearization approach. Using a non-linear substitution of logarithmic type, the emergent quadratic equation is split in various ways. New special solutions involving…

High Energy Physics - Theory · Physics 2010-11-26 Stefan Adrian Carstea , Mihai Visinescu

This article presents a detailed introduction to density-based topology optimisation of fluid flow problems. The goal is to allow new students and researchers to quickly get started in the research area and to skip many of the initial…

Computational Engineering, Finance, and Science · Computer Science 2023-02-03 Joe Alexandersen

We present a formulation of flow matching as variational inference, which we refer to as variational flow matching (VFM). Based on this formulation we develop CatFlow, a flow matching method for categorical data. CatFlow is easy to…

Machine Learning · Computer Science 2025-08-19 Floor Eijkelboom , Grigory Bartosh , Christian Andersson Naesseth , Max Welling , Jan-Willem van de Meent