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The deep linear network (DLN) is a model for implicit regularization in gradient based optimization of overparametrized learning architectures. Training the DLN corresponds to a Riemannian gradient flow, where the Riemannian metric is…

Dynamical Systems · Mathematics 2023-05-12 Nadav Cohen , Govind Menon , Zsolt Veraszto

We consider the inverse problem of determining coefficients appearing in semilinear elliptic equations stated on Riemannian manifolds with boundary given the knowledge of the associated Dirichlet-to-Neumann map. We begin with a negative…

Analysis of PDEs · Mathematics 2024-06-18 Ali Feizmohammadi , Yavar Kian , Lauri Oksanen

We consider questions related to quantizing complex valued functions defined on a locally compact topological group. In the case of bounded functions, we generalize R. Werner's approach to prove the characterization of the associated normal…

Quantum Physics · Physics 2007-08-30 J. Kiukas , P. Lahti , K. Ylinen

In this article we study two classical linear water wave problems, i) normal modes of infinite straight channels of bounded constant cross-section, and ii) trapped longitudinal modes in domains with unbounded constant cross-section. Both…

Fluid Dynamics · Physics 2017-10-16 R. M. Vargas-Magaña , A. A. Minzoni , P. Panayotaros

This paper proposes direct and inverse results for the Dirichlet and Dirichlet to Neumann problems for complex curves with nodal type singularities. As an application, we give a method to reconstruct the conformal structure of a compact…

Complex Variables · Mathematics 2015-06-12 Gennadi Henkin , Vincent Michel

We introduce a new approach to the anisotropic Calder\'on problem, based on a map called Poisson embedding that identifies the points of a Riemannian manifold with distributions on its boundary. We give a new uniqueness result for a large…

Analysis of PDEs · Mathematics 2019-04-05 Matti Lassas , Tony Liimatainen , Mikko Salo

We consider the problem of nonlinear dimensionality reduction: given a training set of high-dimensional data whose ``intrinsic'' low dimension is assumed known, find a feature extraction map to low-dimensional space, a reconstruction map…

Information Theory · Computer Science 2007-07-13 Maxim Raginsky

In this paper we consider Deep Neural Networks (DNNs) with a smooth activation function as surrogates for high-dimensional functions that are somewhat smooth but costly to evaluate. We consider the standard (non-periodic) DNNs as well as…

Numerical Analysis · Mathematics 2026-03-04 Alexander Keller , Frances Y. Kuo , Dirk Nuyens , Ian H. Sloan

We consider the inverse boundary value problem of determining a coefficient function in an elliptic partial differential equation from knowledge of the associated Neumann-Dirichlet-operator. The unknown coefficient function is assumed to be…

Analysis of PDEs · Mathematics 2023-05-17 Bastian Harrach

We derive some bounds which can be viewed as an evidence of increasing stability in the problem of recovering the potential coefficient in the Schr\"odinger equation from the Dirichlet-to-Neumann map in the presence of attenuation, when…

Analysis of PDEs · Mathematics 2013-09-12 Victor Isakov , Jenn-Nan Wang

We review the concept of $\tau$-function for simple analytic curves. The $\tau$-function gives a formal solution to the 2D inverse potential problem and appears as the $\tau$-function of the integrable hierarchy which describes conformal…

High Energy Physics - Theory · Physics 2007-05-23 I. K. Kostov , I. Krichever , M. Mineev-Weinstein , P. Wiegmann , A. Zabrodin

We deal with Calder\'on's problem in a layered anisotropic medium $\Omega\subset\mathbb{R}^n$, $n\geq 3$, with complex anisotropic admittivity $\sigma=\gamma A$, where $A$ is a known Lipschitz matrix-valued function. We assume that the…

Analysis of PDEs · Mathematics 2025-05-02 Sonia Foschiatti , Romina Gaburro , Eva Sincich

We consider non-linear elliptic equations having a measure in the right hand side, of the type $ \divo a(x,Du)=\mu, $ and prove differentiability and integrability results for solutions. New estimates in Marcinkiewicz spaces are also given,…

Analysis of PDEs · Mathematics 2007-07-09 Giuseppe Mingione

It is shown that the correlation functions of the random variables $\det(\lambda - X)$, in which $X$ is a real symmetric $ N\times N$ random matrix, exhibit universal local statistics in the large $N$ limit. The derivation relies on an…

Mathematical Physics · Physics 2009-11-07 E. Brezin , S. Hikami

We show that conformal maps of simply connected domains with an analytic boundary to a unit disk have an intimate relation to the dispersionless 2D Toda integrable hierarchy. The maps are determined by a particular solution to the hierarchy…

High Energy Physics - Theory · Physics 2009-10-31 P. B. Wiegmann , A. Zabrodin

On a $3$-dimensional Riemannian manifold with boundary, we define an analogue of the Dirichlet-to-Neumann map for Beltrami fields, which are the eigenvectors of the curl operator and play a major role in fluid mechanics. This map sends the…

Analysis of PDEs · Mathematics 2024-11-20 Alberto Enciso , Carlos Valero

In this paper we derive rigorously the derivative of the Dirichlet to Neumann map and of the Neumann to Dirichlet map of the conductivity equation with respect to movements of vertices of triangular conductivity inclusions. We apply this…

Analysis of PDEs · Mathematics 2020-12-29 E. Beretta , E. Francini , S. Vessella

Solutions of a system of wave equations are constructed for both homogeneous and inhomogeneous Dirichlet boundary conditions at every regularity level. We prove that boundary observability, and thus boundary exact controllability, at some…

Analysis of PDEs · Mathematics 2024-04-24 Thomas Perrin

In the context of the correspondence between real functions on the unit circle and inner analytic functions within the open unit disk, that was presented in previous papers, we show that the constructions used to establish that…

Complex Variables · Mathematics 2019-02-19 Jorge L. deLyra

We present a simple yet accurate method to compute the adjoint double layer potential, which is used to solve the Neumann boundary value problem for Laplace's equation in three dimensions. An expansion in curvilinear coordinates leads us to…

Numerical Analysis · Mathematics 2023-10-03 J. Thomas Beale , Michael Storm , Svetlana Tlupova