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We present the Maple package TDDS (Thomas Decomposition of Differential Systems). Given a polynomially nonlinear differential system, which in addition to equations may contain inequations, this package computes a decomposition of it into a…

Computational Physics · Physics 2018-11-14 Vladimir P. Gerdt , Markus Lange-Hegermann , Daniel Robertz

Subspace clustering is an important unsupervised clustering approach. It is based on the assumption that the high-dimensional data points are approximately distributed around several low-dimensional linear subspaces. The majority of the…

Machine Learning · Computer Science 2021-12-20 Maryam Abdolali , Nicolas Gillis

This paper presents a general method to construct Poisson integrators, i.e., integrators that preserve the underlying Poisson geometry. We assume the Poisson manifold is integrable, meaning there is a known local symplectic groupoid for…

Mathematical Physics · Physics 2024-04-01 Miguel Vaquero , David Martín de Diego , Jorge Cortés

Semidefinite programs (SDPs) and their solvers are powerful tools with many applications in machine learning and data science. Designing scalable SDP solvers is challenging because by standard the positive semidefinite decision variable is…

Optimization and Control · Mathematics 2024-08-09 Yufan Huang , David F. Gleich

This paper presents a comprehensive survey of methods which can be utilized to search for solutions to systems of nonlinear equations (SNEs). Our objectives with this survey are to synthesize pertinent literature in this field by presenting…

Mathematical Software · Computer Science 2022-08-19 Ilias S. Kotsireas , Panos M. Pardalos , Alexander Semenov , William T. Trevena , Michael N. Vrahatis

This paper aims at investigating necessary (and sufficient) conditions for quasilinear systems of first order PDEs to be Hamiltonian, with non-homogeneous operators of order 1 + 0, also with degenerate leading coefficient. As a byproduct,…

Mathematical Physics · Physics 2023-05-23 Pierandrea Vergallo

Effectively modeling phenomena present in highly nonlinear dynamical systems whilst also accurately quantifying uncertainty is a challenging task, which often requires problem-specific techniques. We present a novel, domain-agnostic…

Machine Learning · Statistics 2021-10-26 Thomas M. McDonald , Mauricio A. Álvarez

For binary outcome models, an endogeneity correction based on nonlinear rank-based transformations is proposed. Identification without external instruments is achieved under one of two assumptions: either the endogenous regressor is a…

Econometrics · Economics 2025-05-06 Alexander Mayer , Dominik Wied

Patterns on numerical semigroups are multivariate linear polynomials, and they are said to be admissible if there exists a numerical semigroup such that evaluated at any nonincreasing sequence of elements of the semigroup gives integers…

Number Theory · Mathematics 2012-11-06 Maria Bras-Amorós , Pedro A. García-Sánchez , Albert Vico-Oton

We represent an algorithm reducing a big class of systems of ($M+1$)-dimensional nonlinear partial differential equations (PDEs) to the systems of $M$-dimensional first order PDEs. Thus, we integrate the original system with respect to only…

Exactly Solvable and Integrable Systems · Physics 2015-05-20 A. I. Zenchuk

The paper contributes to an ongoing effort to extend the conformal bootstrap beyond its traditional focus on systems of four-point correlation functions. Recently, it was demonstrated that semidefinite programming can be used to formulate a…

High Energy Physics - Theory · Physics 2025-12-10 Sebastian Harris

Recent algorithmic advances in algebraic automata theory drew attention to semigroupoids (semicategories). These are mathematical descriptions of typed computational processes, but they have not been studied systematically in the context of…

Formal Languages and Automata Theory · Computer Science 2025-09-30 Attila Egri-Nagy , Chrystopher L. Nehaniv

We study identification and estimation of endogenous linear and nonlinear regression models without excluded instrumental variables, based on the standard mean independence condition and a nonlinear relevance condition. Based on the…

Econometrics · Economics 2023-08-01 Wayne Yuan Gao , Rui Wang

The extended interacting boson model with s-, p-, d-, f- and g-bosons being included (spdfg IBM) are investigated. The algebraic structure including the generators, the Casimir operators of the groups at the SU(5) dynamical symmetry and the…

Nuclear Theory · Physics 2008-11-26 Jing-sheng Li , Yu-xin Liu , Peng Gao

Surrogate models have shown to be an extremely efficient aid in solving engineering problems that require repeated evaluations of an expensive computational model. They are built by sparsely evaluating the costly original model and have…

Machine Learning · Statistics 2022-12-01 M. Moustapha , B. Sudret

In this article we study the differentiability of solutions of parabolic semilinear stochastic evolution equations (SEEs) with respect to their initial values. We prove that if the nonlinear drift coefficients and the nonlinear diffusion…

Probability · Mathematics 2021-11-02 Adam Andersson , Arnulf Jentzen , Ryan Kurniawan , Timo Welti

In both Tweedie and geometric Tweedie models, the common power parameter $p\notin(0,1)$ works as an automatic distribution selection. It mainly separates two subclasses of semicontinuous ($1<p<2$) and positive continuous ($p\geq 2$)…

Methodology · Statistics 2020-01-30 Rahma Abid , Célestin C. Kokonendji

Integrable systems of the sine-Gordon/Liouville type, which arise from reducing the BPS equations for solutions invariant under 16 supersymmetries in Type IIB supergravity and M-theory, are shown to be special cases of an infinite family of…

High Energy Physics - Theory · Physics 2011-02-07 Eric D'Hoker , John Estes

A partial order is called semilinear iff the upper bounds of each element are linearly ordered and any two elements have a common upper bound. There exists, up to isomorphism, a unique countable existentially closed semilinear order, which…

Building upon the concepts and mechanisms used for the development in Moving Points Algorithm, we will now explore how non linear decision boundaries can be developed for classification tasks. First we will look at the classification…

Machine Learning · Computer Science 2025-03-14 Vatsal Srivastava
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