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Representing graphs as sets of node embeddings in certain curved Riemannian manifolds has recently gained momentum in machine learning due to their desirable geometric inductive biases, e.g., hierarchical structures benefit from hyperbolic…

Machine Learning · Computer Science 2020-06-09 Calin Cruceru , Gary Bécigneul , Octavian-Eugen Ganea

In this paper, we consider the problem of fast and efficient indexing techniques for sequences evolving in non-Euclidean spaces. This problem has several applications in the areas of human activity analysis, where there is a need to perform…

Computer Vision and Pattern Recognition · Computer Science 2015-02-17 Rushil Anirudh , Pavan Turaga

Mixed Boolean-Arithmetic (MBA) expressions are frequently used for obfuscation. As they combine arithmetic as well as Boolean operations, neither arithmetic laws nor transformation rules for logical formulas can be applied to suitably…

Cryptography and Security · Computer Science 2022-11-04 Benjamin Reichenwallner , Peter Meerwald-Stadler

We use our Clifford algebra technique, that is nilpotents and projectors which are binomials of the Clifford algebra objects $\gamma^a$ with the property $\{\gamma^a,\gamma^b\}_+ = 2 \eta^{ab}$, for representing quantum gates and quantum…

Quantum Physics · Physics 2009-11-13 M. Gregoric , N. S. Mankoc Borstnik

A class of explicit numerical schemes is developed to solve for the relativistic dynamics and spin of particles in electromagnetic fields, using the Lorentz-BMT equation formulated in the Clifford algebra representation of Baylis. It is…

Computational Physics · Physics 2021-05-05 R. Cabrera , A. G. Campos , D. I. Bondar , S. MacLean , F. Fillion-Gourdeau

The goal of this paper is to introduce a new method in computer-aided geometry of solid modeling. We put forth a novel algebraic technique to evaluate any variadic expression between polyhedral d-solids (d = 2, 3) with regularized operators…

Computational Geometry · Computer Science 2026-01-05 Alberto Paoluzzi , Vadim Shapiro , Antonio DiCarlo , Giorgio Scorzelli , Elia Onofri

In many applications, one encounters signals that lie on manifolds rather than a Euclidean space. In particular, covariance matrices are examples of ubiquitous mathematical objects that have a non Euclidean structure. The application of…

Signal Processing · Electrical Eng. & Systems 2024-07-25 Lucas Drumetz , Alexandre Reiffers-Masson , Naoufal El Bekri , Franck Vermet

In solving hard computational problems, semidefinite program (SDP) relaxations often play an important role because they come with a guarantee of optimality. Here, we focus on a popular semidefinite relaxation of K-means clustering which…

Machine Learning · Computer Science 2018-09-07 Mariano Tepper , Anirvan M. Sengupta , Dmitri Chklovskii

We show how to use Clifford algebra techniques to describe the de Rham cohomology ring of equal rank compact symmetric spaces $G/K$. In particular, for $G/K=U(n)/U(k)\times U(n-k)$, we obtain a new way of multiplying Schur polynomials,…

Representation Theory · Mathematics 2024-11-19 Kieran Calvert , Karmen Grizelj , Andrey Krutov , Pavle Pandžić

We discuss how transformations in a three dimensional euclidean space can be described in terms of the Clifford algebra $\mathcal{C}\ell_{3,3}$ of the quadratic space $\mathbb{R}^{3,3}$. We show that this algebra describes in a unified way…

General Mathematics · Mathematics 2019-08-23 Jayme Vaz , Stephen Mann

In this paper, we introduce a novel algorithm to solve projected model counting (PMC). PMC asks to count solutions of a Boolean formula with respect to a given set of projected variables, where multiple solutions that are identical when…

Artificial Intelligence · Computer Science 2018-05-16 Johannes K. Fichte , Michael Morak , Markus Hecher , Stefan Woltran

After a brief discussion of the computational complexity of Clifford algebras, we present a new basis for even Clifford algebra Cl(2m) that simplifies greatly the actual calculations and, without resorting to the conventional matrix…

Mathematical Physics · Physics 2009-06-25 Marco Budinich

Real-world applications of computational fluid dynamics often involve the evaluation of quantities of interest for several distinct geometries that define the computational domain or are embedded inside it. For example, design optimization…

Numerical Analysis · Mathematics 2023-08-08 Guglielmo Padula , Francesco Romor , Giovanni Stabile , Gianluigi Rozza

Learning low-dimensional numerical representations from symbolic data, e.g., embedding the nodes of a graph into a geometric space, is an important concept in machine learning. While embedding into Euclidean space is common, recent…

Machine Learning · Computer Science 2024-10-10 Thomas Bläsius , Jean-Pierre von der Heydt , Maximilian Katzmann , Nikolai Maas

Projective geometry provides the preferred framework for most implementations of Euclidean space in graphics applications. Translations and rotations are both linear transformations in projective geometry, which helps when it comes to…

Computational Geometry · Computer Science 2007-05-23 Chris Doran , Anthony Lasenby , Joan Lasenby

A complete approach to reasoning under uncertainty requires support for incremental and interactive formulation and revision of, as well as reasoning with, models of the problem domain capable of representing our uncertainty. We present a…

Artificial Intelligence · Computer Science 2013-04-11 Bruce D'Ambrosio

Here is discussed application of the Weyl pair to construction of universal set of quantum gates for high-dimensional quantum system. An application of Lie algebras (Hamiltonians) for construction of universal gates is revisited first. It…

Quantum Physics · Physics 2009-11-07 Alexander Yu. Vlasov

Mathematical objects are generally abstract and not very approachable. Illustrations and interactive visualizations help both students and professionals to comprehend mathematical material and to work with it. This approach lends itself…

History and Overview · Mathematics 2022-05-16 Martin Skrodzki

One of the major successes in computational biology has been the unification, using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied…

Genomics · Quantitative Biology 2009-11-10 Lior Pachter , Bernd Sturmfels

We present GOFMM (geometry-oblivious FMM), a novel method that creates a hierarchical low-rank approximation, "compression," of an arbitrary dense symmetric positive definite (SPD) matrix. For many applications, GOFMM enables an approximate…

Numerical Analysis · Computer Science 2017-07-04 Chenhan D. Yu , James Levitt , Severin Reiz , George Biros