output
19992022
most citedSolving high-dimensional partial differential equations using deep learning

1.8k citations

Showing 2020Show all

17 papers · 1 filter

math.NA2020★ 15 cited

Exponential Convergence of FEM for Spectral Fractional Diffusion in Polygons

Lehel Banjai, Jens M. Melenk, Christoph Schwab

For the spectral fractional diffusion operator of order in bounded, curvilinear polygonal domains we prove exponential convergence of two classes of discreti…

math.NA2020★ 20 cited

Exponential ReLU Neural Network Approximation Rates for Point and Edge Singularities

Carlo Marcati, Joost A. A. Opschoor, Philipp C. Petersen +1

We prove exponential expressivity with stable ReLU Neural Networks (ReLU NNs) in for weighted analytic function classes in certain polytopal domains , in space dimensio…

math.AP2020★ 1 cited

Weighted analyticity of Hartree-Fock eigenfunctions

Yvon Maday, Carlo Marcati

We prove analytic-type estimates in weighted Sobolev spaces on the eigenfunctions of a class of elliptic and nonlinear eigenvalue problems with singular potentials, which includes…

math.FA2020★ 21 cited

Phase retrieval from sampled Gabor transform magnitudes: Counterexamples

Rima Alaifari, Matthias Wellershoff

We consider the recovery of square-integrable signals from discrete, equidistant samples of their Gabor transform magnitude and show that, in general, signals can not be recovered…

cs.LG2020★ 165 cited

Physics Informed Neural Networks for Simulating Radiative Transfer

Siddhartha Mishra, Roberto Molinaro

We propose a novel machine learning algorithm for simulating radiative transfer. Our algorithm is based on physics informed neural networks (PINNs), which are trained by minimizing…

math.FA2020★ 14 cited

Phase retrieval of bandlimited functions for the wavelet transform

Rima Alaifari, Francesca Bartolucci, Matthias Wellershoff

We study the recovery of square-integrable signals from the absolute values of their wavelet transforms, also called wavelet phase retrieval. We present a new uniqueness result for…

math.OC2020★ 86 cited

Iterative Surrogate Model Optimization (ISMO): An active learning algorithm for PDE constrained optimization with deep neural networks

Kjetil O. Lye, Siddhartha Mishra, Deep Ray +1

We present a novel active learning algorithm, termed as iterative surrogate model optimization (ISMO), for robust and efficient numerical approximation of PDE constrained optimizat…

math.AP2020★ 30 cited

The higher order fractional Calderón problem for linear local operators: uniqueness

Giovanni Covi, Keijo Mönkkönen, Jesse Railo +1

We study an inverse problem for the fractional Schrödinger equation (FSE) with a local perturbation by a linear partial differential operator (PDO) of order smaller than the order…

cs.LG2020★ 82 cited

Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant Representation

Tim De Ryck, Maarten De Vos, Alexander Bertrand

Change point detection (CPD) aims to locate abrupt property changes in time series data. Recent CPD methods demonstrated the potential of using deep learning techniques, but often…

math.NA2020★ 5 cited

Second-order accurate TVD numerical methods for nonlocal nonlinear conservation laws

Ulrik Skre Fjordholm, Adrian Montgomery Ruf

We present a second-order accurate numerical method for a class of nonlocal nonlinear conservation laws called the "nonlocal pair-interaction model" which was recently introduced b…

math.NA2020★ 26 cited

Well-balanced finite volume schemes for nearly steady adiabatic flows

Luc Grosheintz-Laval, Roger Käppeli

We present well-balanced finite volume schemes designed to approximate the Euler equations with gravitation. They are based on a novel local steady state reconstruction. The scheme…

math.NA2020★ 35 cited

Numerical simulations for full history recursive multilevel Picard approximations for systems of high-dimensional partial differential equations

Sebastian Becker, Ramon Braunwarth, Martin Hutzenthaler +2

One of the most challenging issues in applied mathematics is to develop and analyze algorithms which are able to approximately compute solutions of high-dimensional nonlinear parti…

math.AP2020★ 3 cited

Div-Curl Problems and -regular Stream Functions in 3D Lipschitz Domains

Matthias Kirchhart, Erick Schulz

We consider the problem of recovering the divergence-free velocity field of a given vorticity on a bounded…

math.NA2020★ 2 cited

Space-time discontinuous Galerkin approximation of acoustic waves with point singularities

Pratyuksh Bansal, Andrea Moiola, Ilaria Perugia +1

We develop a convergence theory of space-time discretizations for the linear, 2nd-order wave equation in polygonal domains , possibly occupied by piecewise ho…

math.PR2020★ 1 cited

Counterexamples to local Lipschitz and local Hölder continuity with respect to the initial values for additive noise driven SDEs with smooth drift coefficient functions with at most polynomially growing derivatives

Arnulf Jentzen, Benno Kuckuck, Thomas Müller-Gronbach +1

In the recent article [A. Jentzen, B. Kuckuck, T. Müller-Gronbach, and L. Yaroslavtseva, arXiv:1904.05963 (2019)] it has been proved that the solutions to every additive noise driv…

math.AP2020★ 44 cited

Unique continuation property and Poincaré inequality for higher order fractional Laplacians with applications in inverse problems

Giovanni Covi, Keijo Mönkkönen, Jesse Railo

We prove a unique continuation property for the fractional Laplacian when . In addition, we study Poincaré-type inequalities for t…

math.AP2020★ 8 cited

On the conservation of energy in two-dimensional incompressible flows

S. Lanthaler, S. Mishra, C. Parés-Pulido

We prove the conservation of energy for weak and statistical solutions of the two-dimensional Euler equations, generated as strong (in an appropriate topology) limits of the underl…