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Many real-world materials are characterized by a glittery appearance. Reproducing this effect in physically based renderings is a challenging problem due to its discrete nature, especially in real-time applications which require a…

Graphics · Computer Science 2025-04-22 Tom Kneiphof , Reinhard Klein

Dedicated tensor accelerators demonstrate the importance of linear algebra in modern applications. Such accelerators have the potential for impressive performance gains, but require programmers to rewrite code using vendor APIs - a barrier…

Most robot mapping techniques for lidar sensors tessellate the environment into pixels or voxels and assume uniformity of the environment within them. Although intuitive, this representation entails disadvantages: The resulting grid maps…

Computer Vision and Pattern Recognition · Computer Science 2019-10-25 Alexander Schaefer , Lukas Luft , Wolfram Burgard

The geodesic-light-cone (GLC) coordinates are a useful tool to analyse light propagation and observations in cosmological models. In this article, we propose a detailed, pedagogical, and rigorous introduction to this coordinate system,…

General Relativity and Quantum Cosmology · Physics 2016-06-09 Pierre Fleury , Fabien Nugier , Giuseppe Fanizza

Gaussian Splatting has emerged as a powerful representation for high-quality, real-time 3D scene rendering. While recent works extend Gaussians with learnable textures to enrich visual appearance, existing approaches allocate a fixed square…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Sheng-Chi Hsu , Ting-Yu Yen , Shih-Hsuan Hung , Hung-Kuo Chu

We describe the GPU implementation of shifted or multimass iterative solvers for sparse linear systems of the sort encountered in lattice gauge theory. We provide a generic tool that can be used by those without GPU programming experience…

High Energy Physics - Lattice · Physics 2011-02-16 Richard Galvez , Greg van Anders

Linear Graph Convolutional Networks (GCNs) are used to classify the node in the graph data. However, we note that most existing linear GCN models perform neural network operations in Euclidean space, which do not explicitly capture the…

Machine Learning · Computer Science 2024-06-17 Qiuyu Liang , Weihua Wang , Feilong Bao , Guanglai Gao

A model, called the linear transform network (LTN), is proposed to analyze the compression and estimation of correlated signals transmitted over directed acyclic graphs (DAGs). An LTN is a DAG network with multiple source and receiver…

Information Theory · Computer Science 2015-04-15 Naveen Goela , Michael Gastpar

The remarkable properties of the geodesic light-cone (GLC) coordinates allow analytic expressions for the light-cone observables, providing a new non-perturbative way for calculating the effects of inhomogeneities in our Universe. However,…

General Relativity and Quantum Cosmology · Physics 2017-06-07 Fulvio Scaccabarozzi , Jaiyul Yoo

Hierarchical lattices that constitute spatially anisotropic systems are introduced. These lattices provide exact solutions for hierarchical models and, simultaneously, approximate solutions for uniaxially or fully anisotropic d=3 physical…

Statistical Mechanics · Physics 2007-05-23 A. Erbas , A. Tuncer , B. Yucesoy , A. N. Berker

With increasing game size, a problem of computational complexity arises. This is especially true in real world problems such as in social systems, where there is a significant population of players involved in the game, and the complexity…

Computer Science and Game Theory · Computer Science 2016-09-12 Tatsuya Iwase , Takahiro Shiga

We deal with dynamical systems on complex lattices possessing chains of non-transversal heteroclinic connections between several periodic orbits. The systems we consider are inspired by the so-called \emph{toy model systems} (TMS) used to…

Dynamical Systems · Mathematics 2024-06-04 Amadeu Delshams , Piotr Zgliczynski

Providing quantitative interpretation of coherent nonlinear microscopy images, such as third-harmonic generation (THG), is generally hampered by the complex phase-matching conditions, especially in the presence of sample linear…

Optics · Physics 2026-03-09 Mohammad Reza Farhadinia , Nicolas Olivier

When training transformers on graph-structured data, incorporating information about the underlying topology is crucial for good performance. Topological masking, a type of relative position encoding, achieves this by upweighting or…

The distribution of the cosmic convergence field is modeled using a large-deviation principle where all non-Gaussian contributions are computed from first principles. The geometry of the past light cone is accounted for by constructing the…

Cosmology and Nongalactic Astrophysics · Physics 2020-01-22 Alexandre Barthelemy , Sandrine Codis , Cora Uhlemann , Francis Bernardeau , Raphael Gavazzi

Lightweight Temporal Compression (LTC) is among the lossy stream compression methods that provide the highest compression rate for the lowest CPU and memory consumption. As such, it is well suited to compress data streams in…

Information Theory · Computer Science 2018-11-27 Bo Li , Omid Sarbishei , Hosein Nourani , Tristan Glatard

We review a class of methods that can be collected under the name nonlinear transform coding (NTC), which over the past few years have become competitive with the best linear transform codecs for images, and have superseded them in terms of…

This work proposes an automatic real time lighting technique for procedurally generated isometric maps. The scenario is generated from a string seed and the proposed lighting system estimates the geometrical shape of the 2D objects as if…

Graphics · Computer Science 2026-05-19 Érick Oliveira Rodrigues , Esteban Clua

Metasurfaces represent one of the most vibrant fields of modern science and technology. A metasurface is a complex electromagnetic structure, that is typically deeply subwavelength in thickness, electrically large in transverse size and…

Optics · Physics 2017-11-01 Yousef Vahabzadeh , Nima Chamanara , Karim Achouri , Christophe Caloz

Time series classification (TSC) is fundamental in numerous domains, including finance, healthcare, and environmental monitoring. However, traditional TSC methods often struggle with the inherent complexity and variability of time series…

Machine Learning · Computer Science 2026-02-06 Marcell T. Kurbucz , Balázs Hajós , Balázs P. Halmos , Vince Á. Molnár , Antal Jakovác
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