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The computation of Gaussian orthant probabilities has been extensively studied for low-dimensional vectors. Here, we focus on the high-dimensional case and we present a two-step procedure relying on both deterministic and stochastic…

Methodology · Statistics 2018-12-03 Dario Azzimonti , David Ginsbourger

We find expressions of the polynomials defining the dual varieties of Grassmannians $Gr(3,9)$ and $Gr(4,8)$ both in terms of the fundamental invariants and in terms of a generic semi-simple element. We project the polynomial defining the…

Algebraic Geometry · Mathematics 2025-10-16 Frédéric Holweck , Luke Oeding

We describe an algorithm for computing certain characteristic numbers of surface scrolls using degenerations. As a corollary we obtain a method for computing the corresponding Gromov-Witten invariants of Grassmannians.

Algebraic Geometry · Mathematics 2007-05-23 Izzet Coskun

Grassmann cactus variety is a common generalisation of Grassmann secant variety and cactus variety. In their definitions one considers the vector spaces of fixed dimension that are contained in the linear span of some finite schemes. We…

Algebraic Geometry · Mathematics 2026-02-13 Weronika Buczyńska , Jarosław Buczyński , Maciej Gałązka

An exact solution to a family of parity check error-correcting codes is provided by mapping the problem onto a Husimi cactus. The solution obtained in the thermodynamic limit recovers the replica symmetric theory results and provides a very…

Disordered Systems and Neural Networks · Physics 2009-10-31 Renato Vicente , David Saad , Yoshiyuki Kabashima

In this paper, we propose a construction of GLSM defects corresponding to Schubert cycles in Lagrangian Grassmannians, following recent work of Closset-Khlaif on Schubert cycles in ordinary Grassmannians. In the case of Lagrangian…

High Energy Physics - Theory · Physics 2025-06-17 W. Gu , L. Mihalcea , E. Sharpe , W. Xu , H. Zhang , H. Zou

We present a proof of a Littlewood-Richardson rule for the K-theory of odd orthogonal Grassmannians OG(n,2n+1), as conjectured in [Thomas-Yong '09]. Specifically, we prove that rectification using the jeu de taquin for increasing shifted…

Combinatorics · Mathematics 2014-08-27 Edward Clifford , Hugh Thomas , Alexander Yong

The Strong Constraint 4D Variational (SC-4DVAR) data assimilation method is widely used in climate and weather applications. SC-4DVAR involves solving a minimization problem to compute the maximum a posteriori estimate, which we tackle…

Numerical Analysis · Mathematics 2025-06-16 Amit N. Subrahmanya , Vishwas Rao , Arvind K. Saibaba

We prove Pieri formulas for the multiplication with special Schubert classes in the K-theory of all cominuscule Grassmannians. For Grassmannians of type A this gives a new proof of a formula of Lenart. Our formula is new for Lagrangian…

Algebraic Geometry · Mathematics 2010-05-17 Anders Skovsted Buch , Vijay Ravikumar

Generative adversarial networks (GANs) are an exciting alternative to algorithms for solving density estimation problems---using data to assess how likely samples are to be drawn from the same distribution. Instead of explicitly computing…

Machine Learning · Computer Science 2017-09-20 Christopher Grimm , Yuhang Song , Michael L. Littman

We study the complexity of learning $k$-mixtures of Gaussians ($k$-GMMs) on $\mathbb{R}^d$. This task is known to have complexity $d^{\Omega(k)}$ in full generality. To circumvent this exponential lower bound on the number of components,…

Machine Learning · Computer Science 2025-04-22 Ilias Diakonikolas , Daniel M. Kane , Sushrut Karmalkar , Jasper C. H. Lee , Thanasis Pittas

We introduce new hybridizable discontinuous Galerkin (HDG) methods for solving the two-dimensional vector Laplacian equation under three types of boundary conditions: electric, magnetic, and Dirichlet. The method is formulated on a…

Numerical Analysis · Mathematics 2026-04-08 Bernardo Cockburn , Cristhian Núñez , Manuel A. Sánchez

We study the geometry of the secant and tangential variety of a cominuscule and minuscule variety, e.g. a Grassmannian or a spinor variety. Using methods inspired by statistics we provide an explicit local isomorphism with a product of an…

Algebraic Geometry · Mathematics 2016-05-19 Laurent Manivel , Mateusz Michałek

Given a Schubert variety $\mathcal{S}$ contained in a Grassmannian $\mathbb{G}_{k}(\mathbb{C}^{l})$, we show how to obtain further information on the direct summands of the derived pushforward $R \pi_{*} \mathbb{Q}_{\tilde{\mathcal{S}}}$…

Algebraic Geometry · Mathematics 2022-03-22 Francesca Cioffi , Davide Franco , Carmine Sessa

We study higher order determinantal varieties obtained by considering generic $m\times n$ ($m \le n$) matrices over rings of the form $F[t]/(t^k)$, and for some fixed $r$, setting the coefficients of powers of $t$ of all $r \times r$ minors…

Algebraic Geometry · Mathematics 2007-05-23 Tomaz Kosir , B. A. Sethuraman

This paper studies the family of interior penalty discontinuous Galerkin methods for solving the Herrmann formulation of the linear elasticity eigenvalue problem in heterogeneous media. By employing a weighted Lam\'e coefficient norm within…

Numerical Analysis · Mathematics 2024-02-28 Arbaz Khan , Felipe Lepe , Jesus Vellojin

This paper introduces a novel Bayesian approach to detect changes in the variance of a Gaussian sequence model, focusing on quantifying the uncertainty in the change point locations and providing a scalable algorithm for inference. Such a…

Methodology · Statistics 2025-03-04 Lorenzo Cappello , Oscar Hernan Madrid Padilla

In this paper, for the Stokes eigenvalue problem in $d$-dimensional case $(d=2,3)$, we present an a posteriori error estimate of residual type of the mixed discontinuous Galerkin finite element method using $P_{k}-P_{k-1}$ element $(k\geq…

Numerical Analysis · Mathematics 2022-09-14 L. L. Sun , H. Bi , Y. D. Yang

We propose a numerical method to approximate the solution of second order elliptic problems in nonvariational form. The method is of Galerkin type using conforming finite elements and applied directly to the nonvariational (nondivergence)…

Numerical Analysis · Mathematics 2011-05-19 Omar Lakkis , Tristan Pryer

We study the complexity of learning mixtures of separated Gaussians with common unknown bounded covariance matrix. Specifically, we focus on learning Gaussian mixture models (GMMs) on $\mathbb{R}^d$ of the form $P= \sum_{i=1}^k w_i…

Machine Learning · Computer Science 2023-06-23 Ilias Diakonikolas , Daniel M. Kane , Thanasis Pittas , Nikos Zarifis