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Related papers: Normalizing Flows on Tori and Spheres

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Normalizing flows have proven their efficacy for density estimation in Euclidean space, but their application to rotational representations, crucial in various domains such as robotics or human pose modeling, remains underexplored.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Olaf Dünkel , Tim Salzmann , Florian Pfaff

In this paper we examine the flow generated by coupled surface and internal small-amplitude water waves in a two-fluid layer model, where we take the upper layer to be rotational (constant vorticity) and the lower layer to be irrotational.…

Fluid Dynamics · Physics 2026-01-21 David Henry , Rossen I. Ivanov , Zisis N. Sakellaris

We present rectified flow, a surprisingly simple approach to learning (neural) ordinary differential equation (ODE) models to transport between two empirically observed distributions \pi_0 and \pi_1, hence providing a unified solution to…

Machine Learning · Computer Science 2022-09-08 Xingchao Liu , Chengyue Gong , Qiang Liu

In this paper, we provide a classification of steady solutions to two-dimensional incompressible Euler equations in terms of the set of flow angles. The first main result asserts that the set of flow angles of any bounded steady flow in the…

Analysis of PDEs · Mathematics 2024-05-27 Changfeng Gui , Chunjing Xie , Huan Xu

We approach the problem of learning continuous normalizing flows from a dual perspective motivated by entropy-regularized optimal transport, in which continuous normalizing flows are cast as gradients of scalar potential functions. This…

Machine Learning · Computer Science 2020-06-12 Chris Finlay , Augusto Gerolin , Adam M Oberman , Aram-Alexandre Pooladian

In this work, we investigate the use of normalizing flows to model conditional distributions. In particular, we use our proposed method to analyze inverse problems with invertible neural networks by maximizing the posterior likelihood. Our…

Machine Learning · Computer Science 2019-11-07 Zhisheng Xiao , Qing Yan , Yali Amit

We revisit the well-known Curve Shortening Flow for immersed curves in the $d$-dimensional Euclidean space. We exploit a fundamental structure of the problem to derive a new global construction of a solution, that is, a construction that is…

Analysis of PDEs · Mathematics 2023-12-01 Patrick Guidotti

A recently proposed renormalization group technique, based on the hierarchical structures present in theories with fluctuating geometry, is implemented in the model of branched polymers. The renormalization group equations can be solved…

High Energy Physics - Lattice · Physics 2009-10-28 Jan Ambjorn , Piotr Bialas , Jerzy Jurkiewicz

Assuming a-priori a smooth generating vector field, we introduce a generally covariant measure of the flow geometry called the referential gradient of the flow. The main result is the explicit relation between the referential gradient and…

Mathematical Physics · Physics 2014-11-21 J. K. Edmondson

A new important relation between fluid mechanics and differential geometry is established. We study smooth steady solutions to the Euler equations with the additional property: the velocity vector is orthogonal to the gradient of the…

Mathematical Physics · Physics 2023-02-14 Vladimir Yu. Rovenski , Vladimir A. Sharafutdinov

Fluid flows are omnipresent in nature and engineering disciplines. The reliable computation of fluids has been a long-lasting challenge due to nonlinear interactions over multiple spatio-temporal scales. The compressible Navier-Stokes…

Fluid Dynamics · Physics 2021-12-10 Deniz A. Bezgin , Aaron B. Buhendwa , Nikolaus A. Adams

We introduce the notion of Fermi flow for hypersurfaces in Riemannian manifolds. It turns out that this is a powerful tool to study the geometry of distance surfaces about a given initial hypersurface. Some of the results in this paper are…

dg-ga · Mathematics 2008-02-03 Knut Smoczyk

Normalizing flows model a complex target distribution in terms of a bijective transform operating on a simple base distribution. As such, they enable tractable computation of a number of important statistical quantities, particularly…

Machine Learning · Computer Science 2022-09-01 Chandramouli Shama Sastry , Andreas Lehrmann , Marcus Brubaker , Alexander Radovic

Applications of normalizing flows to the sampling of field configurations in lattice gauge theory have so far been explored almost exclusively in two space-time dimensions. We report new algorithmic developments of gauge-equivariant flow…

Solutions of long, flexible polymer molecules are complex fluids that simultaneously exhibit fluid-like and solid-like behaviour. When subjected to external flows, dilute polymer solutions develop elastic turbulence - a unique chaotic flow…

Fluid Dynamics · Physics 2025-09-04 Alexander Morozov , Martin Lellep , Damiano Capocci , Moritz Linkmann

Flows in networks (or graphs) play a significant role in numerous computer vision tasks. The scalar-valued edges in these graphs often lead to a loss of information and thereby to limitations in terms of expressiveness. For example,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-16 Viktoria Ehm , Daniel Cremers , Florian Bernard

In this paper, we consider the mean curvature flow of convex hypersurfaces in Euclidean spaces with a general forcing term. We show that the flow may shrink to a point in finite time if the forcing term is small, or exist for all times and…

Differential Geometry · Mathematics 2008-06-17 Guanghan Li , Isabel Salavessa

In this work, we study and solve the normalized Ricci flow equation for circle bundles over surfaces. Moreover, we study the asymptotic behavior of the solutions and their connections to some model geometries.

Differential Geometry · Mathematics 2025-05-08 Arash Bazdar , Georgios Fotopoulos

Consider a fluid flowing through a junction between two pipes with different sections. Its evolution is described by the 2D or 3D Euler equations, whose analytical theory is far from complete and whose numerical treatment may be rather…

Analysis of PDEs · Mathematics 2009-03-05 Rinaldo M. Colombo , Mauro Garavello

Estimating the causal structure of observational data is a challenging combinatorial search problem that scales super-exponentially with graph size. Existing methods use continuous relaxations to make this problem computationally tractable…

Machine Learning · Computer Science 2024-02-20 Hamidreza Kamkari , Vahid Balazadeh , Vahid Zehtab , Rahul G. Krishnan