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We obtain Gaussian upper bounds for heat kernels of higher order differential operators with Dirichlet boundary conditions on bounded domains in $\R^N$. The bounds exhibit explicitly the nature of the spatial decay of the heat kernel close…

Analysis of PDEs · Mathematics 2012-08-01 Narinder Claire

We obtain an upper heat kernel bound for the Laplacian on metric graphs arising as one skeletons of certain polygonal tilings of the plane, which reflects the one dimensional as well as the two dimensional nature of these graphs.

Analysis of PDEs · Mathematics 2016-07-12 René Pröpper

We provide sharp two-sided estimates on the Dirichlet heat kernel $k_1(t,x,y)$ for the Laplacian in a ball. The result accurately describes the exponential behaviour of the kernel for small times and significantly improves the qualitatively…

Analysis of PDEs · Mathematics 2017-04-05 Jacek Malecki , Grzegorz Serafin

An optimal bound on the quantiles of a certain kind of distributions is given. Such a bound is used in applications to Berry--Esseen-type bounds for nonlinear statistics.

Probability · Mathematics 2013-01-03 Iosif Pinelis

In this paper we obtain significant bounds for the number of maximal subgroups of a given index of a finite group. These results allow us to give new bounds for the number of random generators needed to generate a finite $d$-generated group…

Group Theory · Mathematics 2023-03-14 A. Ballester-Bolinches , R. Esteban-Romero , P. Jiménez-Seral

In this paper, we present upper bounds for the depth of some classes of polyhedra, including: polyhedra with finite fundamental group, polyhedra $P$ with abelian or free $\pi_1(P)$ and finitely generated $H_i(tilde{P};\mathbb{Z}$,…

Algebraic Topology · Mathematics 2023-08-01 Mojtaba Mohareri , Behrooz Mashayekhy

We introduce a novel kernel-based framework for learning differential equations and their solution maps that is efficient in data requirements, in terms of solution examples and amount of measurements from each example, and computational…

Machine Learning · Statistics 2025-04-07 Yasamin Jalalian , Juan Felipe Osorio Ramirez , Alexander Hsu , Bamdad Hosseini , Houman Owhadi

In this paper, we study the statistical properties of kernel $k$-means and obtain a nearly optimal excess clustering risk bound, substantially improving the state-of-art bounds in the existing clustering risk analyses. We further analyze…

Machine Learning · Computer Science 2020-05-15 Yong Liu , Lizhong Ding , Weiping Wang

We prove sharp two-sided global estimates for the heat kernel associated with a Euclidean sphere of arbitrary dimension. This solves a long-standing open problem.

Classical Analysis and ODEs · Mathematics 2019-11-19 Adam Nowak , Peter Sjögren , Tomasz Z. Szarek

We show that the Rouquier dimension of the category of perfect complexes over a regular ring is precisely the Krull dimension of the ring. Previously, it was known that the Krull dimension is an upper bound, the lower bound however was not…

Commutative Algebra · Mathematics 2025-07-01 Janina C. Letz

We prove sharp upper and lower estimates for the parabolic kernel of the singular elliptic operator \begin{align*} \mathcal L&=\mbox{Tr }\left(AD^2\right)+\frac{\left(v,\nabla\right)}y, \end{align*} in the half-space…

Analysis of PDEs · Mathematics 2024-08-02 Luigi Negro , Chiara Spina

We consider the degree-diameter problem for Cayley graphs of dihedral groups. We find upper and lower bounds on the maximum number of vertices of such a graph with diameter 2 and degree $d$. We completely determine the asymptotic behaviour…

Combinatorics · Mathematics 2015-02-17 Grahame Erskine

We address the estimation of "extreme" conditional quantiles i.e. when their order converges to one as the sample size increases. Conditions on the rate of convergence of their order to one are provided to obtain asymptotically Gaussian…

Statistics Theory · Mathematics 2012-12-07 L. Gardes , S. Girard

We give new, explicit and asymptotically sharp, lower bounds for dimensions of irreducible modular representations of finite symmetric groups.

Representation Theory · Mathematics 2019-09-10 Alexander Kleshchev , Lucia Morotti , Pham Huu Tiep

We derive an optimal bound on the sum of entropic uncertainties of two or more observables when they are sequentially measured on the same ensemble of systems. This optimal bound is shown to be greater than or equal to the bounds derived in…

Quantum Physics · Physics 2009-11-07 M. D. Srinivas

Non-conservative uncertainty bounds are key for both assessing an estimation algorithm's accuracy and in view of downstream tasks, such as its deployment in safety-critical contexts. In this paper, we derive a tight, non-asymptotic…

Machine Learning · Computer Science 2026-01-16 Amon Lahr , Johannes Köhler , Anna Scampicchio , Melanie N. Zeilinger

We obtain sharp lower and upper bounds for the number of maximal (under inclusion) independent sets in trees with fixed number of vertices and diameter. All extremal trees are described up to isomorphism.

Combinatorics · Mathematics 2008-12-31 Alexander Dainiak

H\"older estimates and Harnack inequalities are studied for fully nonlinear integro-differential equations under some mild assumptions. We allow the kernels of variable order and critically close to 2.

Analysis of PDEs · Mathematics 2022-07-07 Shuhei Kitano

Kernel Stein discrepancies (KSDs) have emerged as a powerful tool for quantifying goodness-of-fit over the last decade, featuring numerous successful applications. To the best of our knowledge, all existing KSD estimators with known rate…

Machine Learning · Statistics 2026-03-31 Jose Cribeiro-Ramallo , Agnideep Aich , Florian Kalinke , Ashit Baran Aich , Zoltán Szabó

We prove qualitatively sharp heat kernel bounds in the setting of Fourier-Bessel expansions when the associated type parameter $\nu$ is half-integer. Moreover, still for half-integer $\nu$, we also obtain sharp estimates of all kernels…

Classical Analysis and ODEs · Mathematics 2014-10-29 Adam Nowak , Luz Roncal