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Steady fluid flows have very special topology. In this paper we describe necessary and sufficient conditions on the vorticity function of a 2D ideal flow on a surface with or without boundary, for which there exists a steady flow among…

Symplectic Geometry · Mathematics 2015-11-19 Anton Izosimov , Boris Khesin

Mean curvature flow is the most natural evolution equation in extrinsic geometry, and shares many features with Hamilton's Ricci flow from intrinsic geometry. In this lecture series, I will provide an introduction to the mean curvature flow…

Differential Geometry · Mathematics 2024-06-18 Robert Haslhofer

Continuous normalizing flows (CNFs) construct invertible mappings between an arbitrary complex distribution and an isotropic Gaussian distribution using Neural Ordinary Differential Equations (neural ODEs). It has not been tractable on…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Shian Du , Yihong Luo , Wei Chen , Jian Xu , Delu Zeng

Waves with constant vorticity and electrohydrodynamics flows are two topics in fluid dynamics that have attracted much attention from scientists for both the mathematical challenge and their industrial applications. The coupling of electric…

Fluid Dynamics · Physics 2023-01-04 Marcelo V. Flamarion , Tao Gao , Roberto Ribeiro-Jr , Alex Doak

New elementary, self-contained proofs are presented for the topological and the smooth classification theorems of linear flows on finite-dimensional normed spaces. The arguments, and the examples that accompany them, highlight the…

Dynamical Systems · Mathematics 2018-06-12 Arno Berger , Anthony Wynne

In this article, we continue the work in \cite{GL} and study a normalized hypersurface flow in the more general ambient setting of warped product spaces. This flow preserves the volume of the bounded domain enclosed by a graphical…

Differential Geometry · Mathematics 2018-07-18 Pengfei Guan , Junfang Li , Mu-Tao Wang

Normalizing flows are a powerful tool for generative modelling, density estimation and posterior reconstruction in Bayesian inverse problems. In this paper, we introduce proximal residual flows, a new architecture of normalizing flows.…

Machine Learning · Computer Science 2023-05-19 Johannes Hertrich

Spherical accretion flows are simple enough for analytical study, by solution of the corresponding fluid dynamic equations. The solutions of stationary spherical flow are due to Bondi. The questions of the choice of a physical solution and…

General Relativity and Quantum Cosmology · Physics 2009-11-11 Jose Gaite

Normalizing Flows provide a principled framework for high-dimensional density estimation and generative modeling by constructing invertible transformations with tractable Jacobian determinants. We propose Fractal Flow, a novel normalizing…

Machine Learning · Statistics 2025-08-28 Binhui Zhang , Jianwei Ma

The space of couplings of a given theory is the arena of interest in this article. Equipped with a metric ansatz akin to the Fisher information matrix in the space of parameters in statistics (similar metrics in physics are the…

High Energy Physics - Theory · Physics 2009-11-07 Sayan Kar

This paper reports several new classes of weakly unstable recurrent solutions of the 2+1-dimensional Euler equation on a square domain with periodic boundary conditions. These solutions have a number of remarkable properties which…

Fluid Dynamics · Physics 2023-08-31 Dmitriy Zhigunov , Roman O. Grigoriev

Generative modeling seeks to uncover the underlying factors that give rise to observed data that can often be modeled as the natural symmetries that manifest themselves through invariances and equivariances to certain transformation laws.…

Machine Learning · Computer Science 2022-08-16 Avishek Joey Bose , Marcus Brubaker , Ivan Kobyzev

Extracting the maximum amount of cosmological and astrophysical information from upcoming large-scale surveys remains a challenge. This includes evaluating the exact likelihood, parameter inference and generating new diverse synthetic…

Cosmology and Nongalactic Astrophysics · Physics 2022-11-24 Roy Friedman , Sultan Hassan

We present theorems which provide the existence of invariant whiskered tori in finite-dimensional exact symplectic maps and flows. The method is based on the study of a functional equation expressing that there is an invariant torus. We…

Dynamical Systems · Mathematics 2009-03-03 Ernest Fontich , Rafael de la Llave , Yannick Sire

Ptychography, as an essential tool for high-resolution and nondestructive material characterization, presents a challenging large-scale nonlinear and non-convex inverse problem; however, its intrinsic photon statistics create clear…

Machine Learning · Statistics 2021-11-02 Agnimitra Dasgupta , Zichao Wendy Di

We introduce manifold-learning flows (M-flows), a new class of generative models that simultaneously learn the data manifold as well as a tractable probability density on that manifold. Combining aspects of normalizing flows, GANs,…

Machine Learning · Statistics 2020-11-16 Johann Brehmer , Kyle Cranmer

A holomorphic map from the complex line to a complex projective space is called normal (a. k. a. Brody curve) if it is uniformly continuous from the Euclidean metric to the Fubini--Study metric. The paper contains a survey of known results…

Complex Variables · Mathematics 2007-10-08 Alexandre Eremenko

We study the global existence and stability of surface diffusion flow (the normal velocity is given by the Laplacian of the mean curvature) of smooth boundaries of subsets of the $n$--dimensional flat torus. More precisely, we show that if…

Analysis of PDEs · Mathematics 2025-10-07 Antonia Diana , Nicola Fusco , Carlo Mantegazza

Models and simulations of the flow of thin films of fluids have many important applications in industrial and natural processes. We consider the motion of a thin layer of an incompressible, Newtonian fluid over an arbitrary solid,…

patt-sol · Physics 2007-05-23 Zhenquan Li , A. J. Roberts

Normalizing Flows (NFs) are able to model complicated distributions p(y) with strong inter-dimensional correlations and high multimodality by transforming a simple base density p(z) through an invertible neural network under the change of…

Machine Learning · Computer Science 2023-11-14 Christina Winkler , Daniel Worrall , Emiel Hoogeboom , Max Welling
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