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We combine tools from homotopy continuation solvers with the methods of analytic combinatorics in several variables to give the first practical algorithm and implementation for the asymptotics of multivariate rational generating functions…

Combinatorics · Mathematics 2022-09-07 Kisun Lee , Stephen Melczer , Josip Smolčić

Presented is a Julia meta-program that discovers compact theories from data if they exist. It writes candidate theories in Julia and then validates: tossing the bad theories and keeping the good theories. Compactness is measured by a…

Artificial Intelligence · Computer Science 2017-06-22 Mark A. Stalzer

A new kind of numbers called Hyper Space Complex Numbers and its algebras are defined and proved. It is with good properties as the classic Complex Numbers, such as expressed in coordinates, triangular and exponent forms and following the…

General Mathematics · Mathematics 2009-09-29 Shanguang Tan

In this paper, we generalize the well-known hyperbolic numbers to certain numeric structures scaled by the real numbers. Under our scaling of $\mathbb{R}$, the usual hyperbolic numbers are understood to be our 1-scaled hyperbolic numbers.…

Rings and Algebras · Mathematics 2024-01-03 Daniel Alpay , Ilwoo Cho

We present a hierarchical approach for enhancing the robustness of numerical solvers for modelling radiative MHD flows in multi-dimensions. This approach is based on clustering the entries of the global Jacobian in a hierarchical manner…

Mathematical Physics · Physics 2009-11-10 A. A. Hujeirat

Hyperbolic problems can at times be solved employing symbolic arguments. This is especially true for the construction of forward (and backward) fundamental solutions. We formulate a corresponding abstract scheme and illustrate its…

Analysis of PDEs · Mathematics 2023-12-18 Zhuoping Ruan , Ingo Witt

Practically all of the planning research is limited to states represented in terms of Boolean and numeric state variables. Many practical problems, for example, planning inside complex software systems, require far more complex data types,…

Artificial Intelligence · Computer Science 2023-01-02 Mojtaba Elahi , Jussi Rintanen

Time functions with asymptotically hyperbolic geometry play an increasingly important role in many areas of relativity, from computing black-hole perturbations to analyzing wave equations. Despite their significance, many of their…

General Relativity and Quantum Cosmology · Physics 2024-11-25 Anıl Zenginoğlu

A method for dimension reduction with clustering, classification, or discriminant analysis is introduced. This mixture model-based approach is based on fitting generalized hyperbolic mixtures on a reduced subspace within the paradigm of…

Methodology · Statistics 2017-10-09 Katherine Morris , Paul D. McNicholas

Next generation computer architectures will include order of magnitude more intra-node parallelism; however, many application programmers have a difficult time keeping their codes current with the state-of-the-art machines. In this context,…

Computational Engineering, Finance, and Science · Computer Science 2013-08-08 Andy R. Terrel , Kyle T. Mandli

In this article, we introduce the adapted inverse iteration method to generate bicomplex Julia sets associated to the polynomial map $w^2+c$. The result is based on a full characterization of bicomplex Julia sets as the boundary of a…

Dynamical Systems · Mathematics 2015-03-13 C. Matteau , D. Rochon

Consider the Poincare disc model for hyperbolic geometry. In this paper, a convenient computational formula is developed along with an aesthetic geometric interpretation. Two proofs, one geometric and one analytical, of each result are…

Metric Geometry · Mathematics 2007-05-23 Benjamin Aaron Bailey

Hierarchical reinforcement learning deals with the problem of breaking down large tasks into meaningful sub-tasks. Autonomous discovery of these sub-tasks has remained a challenging problem. We propose a novel method of learning sub-tasks…

Machine Learning · Computer Science 2019-02-19 Saket Tiwari , M. Prannoy

We present a new package for Mathematica system, called Libra. Its purpose is to provide convenient tools for the transformation of the first-order differential systems $\partial_i \boldsymbol j = M_i \boldsymbol j$ for one or several…

High Energy Physics - Phenomenology · Physics 2021-07-07 Roman N. Lee

A system of commutative hyperbolic complex numbers in 2 dimensions is studied in this paper. Exponential and trigonometric forms are obtained for these hyperbolic twocomplex numbers. Expressions are given for the elementary functions of…

Complex Variables · Mathematics 2007-05-23 Silviu Olariu

We develop high-order numerical schemes to solve random hyperbolic conservation laws using linear programming. The proposed schemes are high-order extensions of the existing first-order scheme introduced in [{\sc S. Chu, M. Herty, M.…

Numerical Analysis · Mathematics 2025-09-03 Shaoshuai Chu , Michael Herty

This paper describes Convex, a convex optimization modeling framework in Julia. Convex translates problems from a user-friendly functional language into an abstract syntax tree describing the problem. This concise representation of the…

Optimization and Control · Mathematics 2014-10-20 Madeleine Udell , Karanveer Mohan , David Zeng , Jenny Hong , Steven Diamond , Stephen Boyd

Using the bicomplex numbers $\mathbb{T}$ which is a commutative ring with zero divisors defined by $\mathbb{T}=\{w_0 + w_1 i_1 + w_2 i_2 + w_3 j | w_0, w_1, w_2, w_3 \in \mathbb{R}\}$ where $i_{1}^{2} = -1, i_{2}^{2} = -1, j^2 = 1, i_1 i_2…

Quantum Physics · Physics 2013-07-10 Dominic Rochon , Sebastien Tremblay

This paper focuses on the problem of unsupervised alignment of hierarchical data such as ontologies or lexical databases. This is a problem that appears across areas, from natural language processing to bioinformatics, and is typically…

Machine Learning · Computer Science 2020-05-11 David Alvarez-Melis , Youssef Mroueh , Tommi S. Jaakkola

Deep learning in hyperbolic space is quickly gaining traction in the fields of machine learning, multimedia, and computer vision. Deep networks commonly operate in Euclidean space, implicitly assuming that data lies on regular grids. Recent…

Machine Learning · Computer Science 2023-12-20 Max van Spengler , Philipp Wirth , Pascal Mettes
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