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This paper introduces a class of k-nearest neighbor ($k$-NN) estimators called bipartite plug-in (BPI) estimators for estimating integrals of non-linear functions of a probability density, such as Shannon entropy and R\'enyi entropy. The…

Statistics Theory · Mathematics 2012-02-28 Kumar Sricharan , Raviv Raich , Alfred O. Hero

The asymptotic behaviour of the vacuum energy density, ${\bar E}(\theta)$, at $\theta \ra \pm i \infty$ is found out. A new interpretation and a qualitative discussion of the ${\bar E}(\theta)$ behaviour are presented. It is emphasized that…

High Energy Physics - Theory · Physics 2007-05-23 Victor Chernyak

We establish the higher differentiability for the minimizers of the following non-autonomous integral functionals \begin{equation*} \mathcal{F}(u,\Omega):= \, \int_\Omega \sum_{i=1}^{n} \, a_i(x) \lvert u_{x_i} \rvert^{p_i} dx,…

Analysis of PDEs · Mathematics 2025-03-04 Stefania Russo

A new stabilization phenomenon induced by degenerate diffusion is discovered in the context of pinned planar $p$-elasticae. It was known that in the non-degenerate regime $p\in(1,2]$, including the classical case of Euler's elastica, there…

Analysis of PDEs · Mathematics 2025-03-28 Tatsuya Miura , Kensuke Yoshizawa

We investigate density estimation from a $n$-sample in the Euclidean space $\mathbb R^D$, when the data is supported by an unknown submanifold $M$ of possibly unknown dimension $d < D$ under a reach condition. We study nonparametric kernel…

Statistics Theory · Mathematics 2020-11-02 Clément Berenfeld , Marc Hoffmann

This is the first in a series of two papers in which we derive a $\Gamma$-expansion for a two-dimensional non-local Ginzburg-Landau energy with Coulomb repulsion, also known as the Ohta-Kawasaki model in connection with diblock copolymer…

Mathematical Physics · Physics 2013-09-24 Dorian Goldman , Cyrill B. Muratov , Sylvia Serfaty

This paper introduces a probability density estimator based on Green's function identities. A density model is constructed under the sole assumption that the probability density is differentiable. The method is implemented as a binary…

Machine Learning · Statistics 2012-08-22 Peter Kovesarki , Ian C. Brock , A. Elizabeth Nuncio Quiroz

In this note two results are established for energy functionals that are given by the integral of $ W(\mathbf x,\nabla \mathbf u(\mathbf x))$ over $\Omega \subset\mathbb{R}^n$ with $\nabla \mathbf u \in BMO(\Omega;{\mathbb R}^{N\times n})$,…

Analysis of PDEs · Mathematics 2020-05-28 Daniel E. Spector , Scott J. Spector

We provide finite-sample analysis of a general framework for using k-nearest neighbor statistics to estimate functionals of a nonparametric continuous probability density, including entropies and divergences. Rather than plugging a…

Statistics Theory · Mathematics 2016-08-23 Shashank Singh , Barnabás Póczos

In this paper, we are interested in a general type of nonlocal energy, defined on a ball $B_R\subset \mathbb R^n$ for some $R>0$ as \[ \mathcal E (u, B_R)= \iint_{\mathbb R^{2n}\setminus (\mathcal C B_R)^2} F( u(x)-u(y),x-y)\, dx \,…

Analysis of PDEs · Mathematics 2019-12-02 Claudia Bucur

We prove the weak Harnack inequality for the functions $u$ which belong to the corresponding De Giorgi classes $DG^{-}(\Omega)$ under the additional assumption that $u\in L^{s}_{loc}(\Omega)$ with some $s> 0$. In particular, our result…

Analysis of PDEs · Mathematics 2023-12-08 Mariia O. Savchenko , Igor I. Skrypnik , Yevgeniia A. Yevgenieva

For a smooth, bounded domain $\Omega$, $s\in(0,1)$, $p\in \left(1,\frac{n+2s}{n-2s}\right)$ we consider the nonlocal equation $$ \epsilon^{2s} (-\Delta)^s u+u=u^p \quad {\mbox{in}}\Omega $$ with zero Dirichlet datum and a small parameter…

Analysis of PDEs · Mathematics 2014-03-19 Juan Davila , Manuel del Pino , Serena Dipierro , Enrico Valdinoci

Neural density estimators are flexible families of parametric models which have seen widespread use in unsupervised machine learning in recent years. Maximum-likelihood training typically dictates that these models be constrained to specify…

Machine Learning · Statistics 2019-04-12 Charlie Nash , Conor Durkan

The expressions for the energy-weighted sum rule of the isoscalar and isovector coordinate operators are derived based on the second-order fluctuation of the local densities. Conventional derivation of the Thouless theorem for the…

Nuclear Theory · Physics 2019-08-09 Nobuo Hinohara

We establish the local boundedness of the local minimizers $u:\Omega\rightarrow\mathbb{R}^{m}$ of non-uniformly elliptic integrals of the form $\int_{\Omega}f(x,Dv)\,dx$, where $\Omega$ is a bounded open subset of $\mathbb{R}^{n}$…

Analysis of PDEs · Mathematics 2026-02-12 Pasquale Ambrosio , Giovanni Cupini , Elvira Mascolo

Many recent advances in computer vision have demonstrated the impressive power of dense and nonsubmodular energy functions in solving visual labeling problems. However, minimizing such energies is challenging. None of existing techniques…

Computer Vision and Pattern Recognition · Computer Science 2014-05-20 Wei Feng , Jiaya Jia , Zhi-Qiang Liu

Development of the electronic kinetic-energy density functional is a subject of major interest in theoretical physics and chemistry. In this work, the nonlocal kinetic-energy functional is developed in terms of the response function for the…

Chemical Physics · Physics 2022-06-17 Hideaki Takahashi

We consider triplets of densities $(u_1,u_2,u_3)$ minimizing the Dirichlet energy \[\sum_{j=1}^3 \int_{\Omega} |\nabla u_j|^2\,dx \] over a bounded domain $\Omega\subset \mathbb{R}^N$, subject to the partial segregation condition: \[…

Analysis of PDEs · Mathematics 2024-11-01 Nicola Soave , Susanna Terracini

We derive, via simultaneous homogenization and dimension reduction, the $\Gamma$-limit for thin elastic plates of thickness $h$ whose energy density oscillates on a scale $\eh$ such that $ \eh^2 \ll h\ll \eh$. We consider the energy scaling…

Analysis of PDEs · Mathematics 2014-10-09 Igor Velcic

We provide a general treatment of perturbations of a class of functionals modeled on convolution energies with integrable kernel which approximate the $p$-th norm of the gradient as the kernel is scaled by letting a small parameter…

Analysis of PDEs · Mathematics 2020-07-09 Roberto Alicandro , Nadia Ansini , Andrea Braides , Andrey Piatnitski , Antonio Tribuzio