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Bayesian networks are a widely-used class of probabilistic graphical models capable of representing symmetric conditional independence between variables of interest using the topology of the underlying graph. For categorical variables, they…

Machine Learning · Statistics 2022-10-07 Gherardo Varando , Federico Carli , Manuele Leonelli

We study locally finite varieties (=primitive classes) of linear algebras over finite fields. We do not assume that our algebras are associative or Lie. We are interested in the basic properties of finite algebras in these varieties such…

Rings and Algebras · Mathematics 2026-03-11 Yuri Bahturin , Alexander Olshanskii

We present simple to implement Wald-type statistics that deliver a general nonparametric inference theory for linear restrictions on varying coefficients in a range of regression models allowing for cross-sectional or spatial dependence. We…

Econometrics · Economics 2026-01-27 Abhimanyu Gupta , Xi Qu , Sorawoot Srisuma , Jiajun Zhang

We consider a generalisation of vector fields on a vector space, where the vector space is generalised to a highest-weight module over a Kac-Moody algebra. The generalised vector field is an element in a non-associative superalgebra defined…

High Energy Physics - Theory · Physics 2026-05-05 Martin Cederwall , Jakob Palmkvist

For a simplicial manifold we construct the differential geometry structure and use it to investigate linear connections, metric and gravity. We discuss and compare three main approaches and calculate the resulting gravity action…

High Energy Physics - Theory · Physics 2008-02-03 Andrzej Sitarz

We define a class of properties on random plane trees, which we call subtree additive properties, inspired by the combinatorics of certain biologically-interesting properties in a plane tree model of RNA secondary structure. The class of…

Combinatorics · Mathematics 2021-01-15 Anna Kirkpatrick , Chidozie Onyeze

Recently, many machine learning and statistical models such as non-linear regressions, the Single Index, Multi-index, Varying Coefficient Index Models and Two-layer Neural Networks can be reduced to or be seen as a special case of a new…

Machine Learning · Computer Science 2020-10-20 Di Wang , Xiangyu Guo , Chaowen Guan , Shi Li , Jinhui Xu

In linear regression problems with related predictors, it is desirable to do variable selection and estimation by maintaining the hierarchical or structural relationships among predictors. In this paper we propose non-negative garrote…

Applications · Statistics 2010-11-03 Ming Yuan , V. Roshan Joseph , Hui Zou

We make an attempt to develop "noncommutative algebraic geometry" in which noncommutative affine schemes are in one-to-one correspondence with associative algebras. In the first part we discuss various aspects of smoothness in affine…

Algebraic Geometry · Mathematics 2016-09-07 Maxim Kontsevich , Alexander Rosenberg

Pseudo-Riemannian metrics with Levi-Civita connection in the projective class of a given torsion free affine connection can be obtained from (and are equivalent to) the maximal rank solutions of a certain overdetermined projectively…

Differential Geometry · Mathematics 2018-03-05 Keegan J. Flood , A. Rod Gover

The Standard Model of the theory of elementary particles is based on the $U(1)\times SU(2)\times SU(3)$ symmetry. In the presence of a gravitation field, i. e. in a non-flat space-time manifold, this symmetry is implemented through three…

Differential Geometry · Mathematics 2007-05-23 Ruslan Sharipov

We consider a complex singlet scalar in the spectral action approach to the standard model. It is shown that there is a range of initial values at the unification scale which is able to produce Higgs and top quark masses at low energies.…

High Energy Physics - Phenomenology · Physics 2017-12-11 Hosein Karimi Khozani

After introducing a noncommutative counterpart of commutative algebraic geometry based on monoidal categories of quasi-coherent sheaves we show that various constructions in noncommutative geometry (e.g. Morita equivalences, Hopf-Galois…

Algebraic Geometry · Mathematics 2007-07-16 Tomasz Maszczyk

A curious correspondence has been known between Landau models and non-linear sigma models: Reinterpreting the base-manifolds of Landau models as field-manifolds, the Landau models are transformed to non-linear sigma models with same global…

High Energy Physics - Theory · Physics 2020-12-16 Kazuki Hasebe

Nonlinear regression analysis is a popular and important tool for scientists and engineers. In this article, we introduce theories and methods of nonlinear regression and its statistical inferences using the frequentist and Bayesian…

Methodology · Statistics 2024-02-09 Hsin-Hsiung Huang , Qing He

We present an integrated approach for structure and parameter estimation in latent tree graphical models. Our overall approach follows a "divide-and-conquer" strategy that learns models over small groups of variables and iteratively merges…

Machine Learning · Computer Science 2019-12-19 Furong Huang , Niranjan U. N. , Ioakeim Perros , Robert Chen , Jimeng Sun , Anima Anandkumar

This paper is focused on nonlinear prediction coding, which consists on the prediction of a speech sample based on a nonlinear combination of previous samples. It is known that in the generation of the glottal pulse, the wave equation does…

Sound · Computer Science 2022-04-01 Marcos Faundez-Zanuy , Enric Monte , Francesc Vallverdú

Left-right symmetric models are analyzed in the context of noncommutative geometry where we show that spontaneous parity violation is ruled out.

High Energy Physics - Theory · Physics 2007-05-23 Florian Girelli

We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models (McGLMs), designed to handle multivariate response variables, along with a wide range of temporal and spatial…

Methodology · Statistics 2017-04-25 Wagner Hugo Bonat , Bent Jørgensen

The properties of scale-free random trees are investigated using both preconditioning on non-extinction and fixed size averages, in order to study the thermodynamic limit. The scaling form of volume probability is found, the connectivity…

Other Condensed Matter · Physics 2009-11-10 Luca Donetti , Claudio Destri
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