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Identifying low-dimensional structure in high-dimensional probability measures is an essential pre-processing step for efficient sampling. We introduce a method for identifying and approximating a target measure $\pi$ as a perturbation of a…

Machine Learning · Statistics 2025-11-19 Matthew T. C. Li , Tiangang Cui , Fengyi Li , Youssef Marzouk , Olivier Zahm

Bobkov (J. Theoret. Probab. 18(2) (2005) 399-412) investigated an approximate de Finetti representation for probability measures, on product measurable spaces, which are symmetric under permutations of coordinates. One of the main results…

Probability · Mathematics 2014-01-03 Bero Roos

Accurate determination of nuclear fission barrier heights is essential for understanding nuclear stability, fission dynamics, and nucleosynthesis. However, theoretical models such as the Extended Thomas-Fermi plus Strutinsky Integral…

Nuclear Theory · Physics 2026-04-21 Kun Ratha Kean , Yoritaka Iwata

Weight space learning aims to extract information about a neural network, such as its training dataset or generalization error. Recent approaches learn directly from model weights, but this presents many challenges as weights are…

Machine Learning · Computer Science 2025-10-23 Jonathan Kahana , Eliahu Horwitz , Imri Shuval , Yedid Hoshen

The author regrets that after discussion of the results with B. L. Feigin a serious error has shown up. The proof of the results we presented in the paper is wrong. We thank B. L. Feigin for the discussion.

Mathematical Physics · Physics 2011-08-31 Friedrich Wagemann

Motivated by the work of Chudnovsky and the Eisenbud-Mazur Conjecture on evolutions, Harbourne and Huneke give a series of conjectures that relate symbolic and regular powers of ideals of fat points in $\mathbb P^n$. The conjectures involve…

Commutative Algebra · Mathematics 2014-04-01 Susan M. Cooper , Stephen G. Hartke

We study inverse problems for the Einstein equations with source fields in a general form. Under a microlocal linearization stability condition, we show that by generating small gravitational perturbations and measuring the responses near a…

Analysis of PDEs · Mathematics 2018-06-19 Gunther Uhlmann , Yiran Wang

Using the twistor correspondence, we give a classification of toric anti-self-dual Einstein metrics: each such metric is essentially determined by an odd holomorphic function. This explains how the Einstein metrics fit into the…

Differential Geometry · Mathematics 2017-03-24 Joel Fine

The goal of this text is to understand and prove a formula stated by Salmon, which gives the first terms of some Taylor expansion of the discriminant of a plane algebraic curve. Salmon uses his formula to derive various enumerative…

Algebraic Geometry · Mathematics 2025-12-10 Laurent Busé , Thomas Dedieu

The Einstein-Langevin equation is a perturbative correction to the semiclassical Einstein equation which takes into account the lowest order quantum fluctuations of the matter stress-energy tensor. It predicts classical stochastic…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Rosario Martin , Enric Verdaguer

On a compact $n$-dimensional manifold $M$, it is well known that a critical metric of the total scalar curvature, restricted to the space of metrics with unit volume, is Einstein. It has been conjectured that a critical metric of the total…

Differential Geometry · Mathematics 2018-01-04 Gabjin Yun , Seungsu Hwang

In both real and complex cases, we establish the connection of the problem about $2$-dimensional linear subspaces the most deviating from the coordinate ones with one simply formulated optimization problem for isoperimetric polygons in…

Numerical Analysis · Mathematics 2024-08-30 Yuri Nesterenko

To each associative unitary finite-dimensional algebra over a normal base, we associative a canonical multiplicative function called its determinant. We give various properties of this construction, as well as applications to the topology…

Algebraic Geometry · Mathematics 2007-12-13 Matthieu Romagny

In this paper, we study invariant Einstein metrics on Ledger-Obata spaces $F^m/\operatorname{diag}(F)$. In particular, we classify invariant Einstein metrics on $F^4/\operatorname{diag}(F)$ and estimate the number of invariant Einstein…

Differential Geometry · Mathematics 2017-02-22 Zhiqi Chen , Yuriĭ Nikonorov , Yulia Nikonorova

The goal of this thesis is to study the use of the Kantorovich-Rubinstein distance as to build a descriptor of sample complexity in classification problems. The idea is to use the fact that the Kantorovich-Rubinstein distance is a metric in…

Probability · Mathematics 2023-09-19 Gaël Giordano

We consider the problem of linear estimation, and establish an extension of the Gauss-Markov theorem, in which the bias operator is allowed to be non-zero but bounded with respect to a matrix norm of Schatten type. We derive simple and…

Machine Learning · Computer Science 2023-11-21 Simon Segert

We give a "soft" proof of Alberti's Luzin-type theorem in [1] (G. Alberti, A Lusintype theorem for gradients, J. Funct. Anal. 100 (1991)), using elementary geometric measure theory and topology. Applications to the $C^2$-rectifiability…

Analysis of PDEs · Mathematics 2026-01-30 Siran Li

We give an analog of Frobenius' theorem about the factorization of the group determinant on the group algebra of finite abelian groups and we extend it into dihedral groups and generalized quaternion groups. Furthermore, we describe the…

Representation Theory · Mathematics 2014-05-09 N. Yamaguchi

Evaluation of the Voigt function, a convolution of a Lorentzian and a Gaussian profile, is essential in various fields such as spectroscopy, atmospheric science, and astrophysics. Efficient computation of the function is crucial, especially…

Instrumentation and Methods for Astrophysics · Physics 2024-11-05 Mofreh R. Zaghloul , Jacques Le Bourlot

The concept of Lyapunov exponent has long occupied a central place in the theory of Anderson localisation; its interest in this particular context is that it provides a reasonable measure of the localisation length. The Lyapunov exponent…

Disordered Systems and Neural Networks · Physics 2013-08-20 Alain Comtet , Christophe Texier , Yves Tourigny