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A new method for constructing self-referential tilings of Euclidean space from a graph directed iterated function system, based on a combinatorial structure we call a pre-tree, is introduced. In the special case that we refer to as…

Metric Geometry · Mathematics 2019-12-06 Michael Barnsley , Andrew Vince

Faster rendering of synthetic images is a core problem in the field of computer graphics. Rendering algorithms, such as path-tracing is dependent on parameters like size of the image, number of light bounces, number of samples per pixel,…

Graphics · Computer Science 2023-06-29 Annada Prasad Behera , Subhankar Mishra

Natural systems are typically nonlinear and complex, and it is of great interest to be able to reconstruct a system in order to understand its mechanism, which can not only recover nonlinear behaviors but also predict future dynamics. Due…

Chaotic Dynamics · Physics 2017-11-03 Huanfei Ma , Siyang Leng , Luonan Chen

Learning rules -- prescriptions for updating model parameters to improve performance -- are typically assumed rather than derived. Why do some learning rules work better than others, and under what assumptions can a given rule be considered…

Machine Learning · Computer Science 2025-11-03 John J. Vastola , Samuel J. Gershman , Kanaka Rajan

New results on the convexity of geodesic-length functions on Teichm\"{u}ller space are presented. A formula for the Hessian of geodesic-length is presented. New bounds for the gradient and Hessian of geodesic-length are described. A…

Differential Geometry · Mathematics 2007-05-23 Scott A. Wolpert

We propose a novel method to reconstruct volumetric flows from sparse views via a global transport formulation. Instead of obtaining the space-time function of the observations, we reconstruct its motion based on a single initial state. In…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Aleksandra Franz , Barbara Solenthaler , Nils Thuerey

Despite their effective use in various fields, many aspects of neural networks are poorly understood. One important way to investigate the characteristics of neural networks is to explore the loss landscape. However, most models produce a…

Machine Learning · Computer Science 2022-04-12 Aleksandar Doknic , Torsten Möller

We study geodesics in the random metric space called the Brownian map, which appears as the scaling limit of large planar maps. In particular, we completely describe geodesics starting from the distinguished point called the root, and we…

Probability · Mathematics 2008-05-30 Jean-Francois Le Gall

We investigate how a residual network can learn to predict the dynamics of interacting shapes purely as an image-to-image regression task. With a simple 2d physics simulator, we generate short sequences composed of rectangles put in motion…

Computer Vision and Pattern Recognition · Computer Science 2016-11-28 François Fleuret

In this paper, we propose new structured second-order methods and structured adaptive-gradient methods obtained by performing natural-gradient descent on structured parameter spaces. Natural-gradient descent is an attractive approach to…

Machine Learning · Statistics 2022-02-22 Wu Lin , Frank Nielsen , Mohammad Emtiyaz Khan , Mark Schmidt

We show that if a subset $\Psi$ of the ends of a graph $G$ can be displayed by a tree-decomposition of finite adhesion, then it can also be displayed by a linked such tree-decomposition. This tree-decomposition captures all combinatorial…

Combinatorics · Mathematics 2025-12-16 Sandra Albrechtsen , Max Pitz , Roman Schaut

We propose an approach to 3D reconstruction via inverse procedural modeling and investigate two variants of this approach. The first option consists in the fitting set of input parameters using a genetic algorithm. We demonstrate the…

Graphics · Computer Science 2023-10-23 Albert Garifullin , Nikolay Maiorov , Vladimir Frolov

Reconstructing object geometry and material from multiple views typically requires optimization. Differentiable path tracing is an appealing framework as it can reproduce complex appearance effects. However, it is difficult to use due to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-09 Purvi Goel , Loudon Cohen , James Guesman , Vikas Thamizharasan , James Tompkin , Daniel Ritchie

We address the inverse problem of reconstructing both the structure and dynamics of a network from mean-field measurements, which are linear combinations of node states. This setting arises in applications where only a few aggregated…

Dynamical Systems · Mathematics 2025-11-04 Narcicegi Kiran , Tiago Pereira

Given a space it is easy to obtain the system of geodesic equations on it. In this paper the inverse problem of reconstructing the space from the geodesic equations is addressed. A procedure is developed for obtaining the metric tensor from…

Differential Geometry · Mathematics 2009-11-13 E. Fredericks , F. M. Mahomed , E. Momoniat , Asghar Qadir

We present a novel 3D pose refinement approach based on differentiable rendering for objects of arbitrary categories in the wild. In contrast to previous methods, we make two main contributions: First, instead of comparing real-world images…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Alexander Grabner , Yaming Wang , Peizhao Zhang , Peihong Guo , Tong Xiao , Peter Vajda , Peter M. Roth , Vincent Lepetit

The two-dimensional surface of a bi-axial ellipsoid is characterized by the lengths of its major and minor axes. Longitude and latitude span an angular coordinate system across. We consider the egg-shaped surface of constant altitude above…

Metric Geometry · Mathematics 2022-12-13 Richard J. Mathar

The stationary isotropic Poisson line process was used to derive upper bounds on mean excess network geodesic length in Aldous and Kendall [Adv. in Appl. Probab. 40 (2008) 1-21]. The current paper presents a study of the geometry and…

Probability · Mathematics 2012-11-08 Wilfrid S. Kendall

We consider Teichm\"uller geodesics in strata of translation surfaces. We prove lower and upper bounds for the Hausdorff dimension of the set of parameters generating a geodesic bounded in some compact part of the stratum. Then we compute…

Dynamical Systems · Mathematics 2023-05-26 Luca Marchese , Rodrigo Treviño , Steffen Weil

Given a trivalent graph in the 3-dimensional Euclidean space, we call it a discrete surface because it has a tangent space at each vertex determined by its neighbor vertices. To abstract a continuum object hidden in the discrete surface, we…

Differential Geometry · Mathematics 2022-03-31 Motoko Kotani , Hisashi Naito , Chen Tao