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Existing methods for quantifying predictive uncertainty in neural networks are either computationally intractable for large language models or require access to training data that is typically unavailable. We derive a lightweight…

Machine Learning · Computer Science 2026-04-01 Nils Grünefeld , Jes Frellsen , Christian Hardmeier

The most common way to sample from a probability distribution is to use Monte-Carlo methods. For distributions on a continuous state space, one can find diffusions with the target distribution as equilibrium measure, so that the state of…

Probability · Mathematics 2015-10-28 Chii-Ruey Hwang , Raoul Normand , Sheng-Jhih Wu

In comparative studies, such as in causal inference and clinical trials, balancing important covariates is often one of the most important concerns for both efficient and credible comparison. However, chance imbalance still exists in many…

Methodology · Statistics 2018-07-30 Yichen Qin , Yang Li , Wei Ma , Feifang Hu

The field of machine have seen rising applications of equivariance criterion. However, there is no systematic way to justify its usage, including why it works, whether there is an optimal solution and if so, what form it carries. In this…

Statistics Theory · Mathematics 2025-09-23 Daowei Wang , Mian Wu , Haojin Zhou

The original motivation for this paper was to provide an efficient quantitative analysis of convex infinite (or semi-infinite) inequality systems whose decision variables run over general infinite-dimensional (resp. finite-dimensional)…

Optimization and Control · Mathematics 2011-02-11 M. J. Cánovas , M. A. LóPez , B. S. Mordukhovich , J. Parra

This paper provides new summation inequalities in both single and double forms to be used in stability analysis of discrete-time systems with time-varying delays. The potential capability of the newly derived inequalities is demonstrated by…

Optimization and Control · Mathematics 2016-06-02 Le Van Hien , Hieu Trinh

Stability is a key property of both forward models and inverse problems, and depends on the norms considered in the relevant function spaces. For instance, stability estimates for hyperbolic partial differential equations are often based on…

Analysis of PDEs · Mathematics 2026-04-13 Rima Alaifari , Giovanni S. Alberti , Tandri Gauksson

We present a novel space-time isogeometric discretization of the acoustic wave equation in second-order formulation that is intrinsically unconditionally stable. The method relies on a variational framework inspired by [Walkington 2014],…

Numerical Analysis · Mathematics 2025-06-19 Matteo Ferrari , Ilaria Perugia

In a Riemannian manifold with a smooth positive function that weights the associated Hausdorff measures we study stable sets, i.e., second order minima of the weighted perimeter under variations preserving the weighted volume. By assuming…

Differential Geometry · Mathematics 2020-07-28 César Rosales

We present a variational principle governing the quasistatic evolution of a linearized elastoplastic material. In case of linear hardening, the novel characterization allows to recover and partly extend some known results and proves itself…

Analysis of PDEs · Mathematics 2007-10-15 Ulisse Stefanelli

Robustness of linear systems with constant coefficients is considered. There exist methods and tools for analyzing the stability of systems with random or deterministic uncertainties. At the same time, there are no approaches for the…

Optimization and Control · Mathematics 2020-12-08 Andrey Tremba

We introduce a mod $n$ covering based approach to stable systolic inequalities. The idea is to prescribe a cohomology class mod $n$ which forces the desired cup product or index to be nonzero, and then find a short integral lift of that…

Differential Geometry · Mathematics 2026-05-19 Aditya Kumar

We study space--time isogeometric discretizations of the linear acoustic wave equation that use splines of arbitrary degree p, both in space and time. We propose a space--time variational formulation that is obtained by adding a…

Numerical Analysis · Mathematics 2024-08-02 Sara Fraschini , Gabriele Loli , Andrea Moiola , Giancarlo Sangalli

We prove three related quantitative results for the relative isoperimetric problem outside a convex body $\Omega$ in the plane: (1) {\L}ojasiewicz estimates and quantitative rigidity for critical points, (2) rates of convergence for the…

Analysis of PDEs · Mathematics 2025-12-02 Elena Mäder-Baumdicker , Robin Neumayer , Jiewon Park , Melanie Rupflin

We address the problem of estimating steady-state quantities associated to systems of stochastic chemical kinetics. In most cases of interest these systems are analytically intractable, and one has to resort to computational methods to…

Quantitative Methods · Quantitative Biology 2014-01-21 Andreas Milias-Argeitis , John Lygeros , Mustafa Khammash

We prove the sharp quantitative isoperimetric inequality in the case of the barycentric asymmetry, for bounded sets. This generalizes the $2$-D case recently proved in~\cite{BCH}.

Functional Analysis · Mathematics 2024-05-29 Chiara Gambicchia , Aldo Pratelli

We study $\varepsilon$-stability in continuous logic. We first consider stability in a model, where we obtain a definability of types result with a better approximation than that in the literature. We also prove forking symmetry for…

Logic · Mathematics 2024-11-08 Nicolas Chavarria

The weak maximum principle of the isoparametric finite element method is proved for the Poisson equation under the Dirichlet boundary condition in a (possibly concave) curvilinear polyhedral domain with edge openings smaller than $\pi$,…

Numerical Analysis · Mathematics 2023-03-17 Buyang Li , Weifeng Qiu , Yupei Xie , Wenshan Yu

In this paper, we study randomized methods for feedback design of uncertain systems. The first contribution is to derive the sample complexity of various constrained control problems. In particular, we show the key role played by the…

Systems and Control · Computer Science 2014-07-22 T. Alamo , R. Tempo , A. Luque , D. R. Ramirez

This paper studies the Hardy-type inequalities on the discrete intervals. The first result is the variational formulas of the optimal constants. Using these formulas, one may obtain an approximating procedure and the known basic estimates…

Functional Analysis · Mathematics 2014-06-24 Zhong-Wei Liao