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We present an algebraic approach to evolutionary accumulation modelling (EvAM). EvAM is concerned with learning and predicting the order in which evolutionary features accumulate over time. Our approach is complementary to the more common…

Applications · Statistics 2026-04-29 Jessica Renz , Frederik Witt , Iain G. Johnston

We consider positive solutions to parametrized systems of generalized polynomial equations (with real exponents and positive parameters). By a fundamental result obtained in parallel work, polynomial systems are determined by geometric…

Algebraic Geometry · Mathematics 2024-10-07 Stefan Müller , Georg Regensburger

New approaches to the theory of dynamic programming view dynamic programs as families of policy operators acting on partially ordered sets. In this paper, we extend these ideas by shifting from arbitrary partially ordered sets to ordered…

Optimization and Control · Mathematics 2026-02-02 Nisha Peng , John Stachurski

Probabilistic solvers for ordinary differential equations (ODEs) have emerged as an efficient framework for uncertainty quantification and inference on dynamical systems. In this work, we explain the mathematical assumptions and detailed…

Machine Learning · Statistics 2021-10-25 Nicholas Krämer , Nathanael Bosch , Jonathan Schmidt , Philipp Hennig

We study sum of squares (SOS) relaxations to optimize polynomial functions over a set $V\cap R^n$, where $V$ is a complex algebraic variety. We propose a new methodology that, rather than relying on some algebraic description, represents…

Optimization and Control · Mathematics 2017-11-21 Diego Cifuentes , Pablo A. Parrilo

We show how to use the method of orthogonal polynomials for integrating, in the planar approximation, the partition function of one-matrix models with a potential with even or odd vertices, or any combination of them.

High Energy Physics - Theory · Physics 2007-05-23 E. Minguzzi

We consider the vectorial system \[ \begin{cases} Du \in \mathcal{O}(2), & \mbox{a.e. in}\;\Omega, u=0, & \mbox{on} \;\partial \Omega, \end{cases} \] where $\Omega$ is a subset of $\R^2$, $u:\Omega\to \R^2$ and $\mathcal{O}(2)$ is the…

Optimization and Control · Mathematics 2017-03-14 Gisella Croce , Giovanni Pisante

This survey paper was primarily written as as the support for a course pesented at the JNCF2025: it aims to present some material that illustrates the kind of estimates one can obtain in effective algebraic geometry, for affine polynomial…

Algebraic Geometry · Mathematics 2026-01-19 Teresa Krick

Variational Bayes (VB) has shown itself to be a powerful approximation method in many application areas. This paper describes some diagnostics methods which can assess how well the VB approximates the true posterior, particularly with…

Computation · Statistics 2013-09-23 Hui Zhao , Paul Marriott

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

We present algorithms for computing zero-dimensional tropical varieties as implemented in OscarZerodimensionalTropicalization.jl. The algorithms include a mathematical workaround for a common practical issue arising when working with…

Algebraic Geometry · Mathematics 2025-12-01 Arman Marti-Shahandeh , Yue Ren , Victoria Schleis

Quantile-based classifiers can classify high-dimensional observations by minimising a discrepancy of an observation to a class based on suitable quantiles of the within-class distributions, corresponding to a unique percentage for all…

Methodology · Statistics 2024-04-23 Marco Berrettini , Christian Hennig , Cinzia Viroli

Linear exact modeling is a problem coming from system identification: Given a set of observed trajectories, the goal is find a model (usually, a system of partial differential and/or difference equations) that explains the data as precisely…

Optimization and Control · Mathematics 2011-10-26 Kristina Schindelar , Viktor Levandovskyy , Eva Zerz

In this paper, we present a novel approach to synthesize invariant clusters for polynomial programs. An invariant cluster is a set of program invariants that share a common structure, which could, for example, be used to save the needs for…

Systems and Control · Computer Science 2022-03-16 Qiuye Wang , Lihong Zhi , Naijun Zhan , Bai Xue , Zhi-hong Yang

We use the implicitization procedure to generate polynomial equality constraints on the set of distributions induced by local interventions on variables governed by a causal Bayesian network with hidden variables. We show how we may reduce…

Artificial Intelligence · Computer Science 2012-06-26 Changsung Kang , Jin Tian

Valuation networks have been proposed as graphical representations of valuation-based systems (VBSs). The VBS framework is able to capture many uncertainty calculi including probability theory, Dempster-Shafer's belief-function theory,…

Artificial Intelligence · Computer Science 2013-03-08 Prakash P. Shenoy

A broad class of informationally complete symmetric measurements is introduced. It can be understood as a common generalization of symmetric, informationally complete POVMs and mutually unbiased bases. Additionally, it provides a natural…

Quantum Physics · Physics 2022-04-27 Katarzyna Siudzińska

The main mathematical focus of this paper is a class of parametrised polynomial systems that we refer to as being tropically transverse. We show how their generic number of solutions can be expressed as the mixed volume of a modified…

Algebraic Geometry · Mathematics 2023-12-01 Isaac Holt , Yue Ren

We study homomorphism polynomials, which are polynomials that enumerate all homomorphisms from a pattern graph $H$ to $n$-vertex graphs. These polynomials have received a lot of attention recently for their crucial role in several new…

Computational Complexity · Computer Science 2020-11-17 Balagopal Komarath , Anurag Pandey , C. S. Rahul

This paper provides a closed form expression for the pairwise score vector for the multivariate ordered probit model. This result has several implications in likelihood-based inference. It is indeed used both to speed-up gradient based…

Methodology · Statistics 2019-01-30 Martina Bravo , Antonio Canale