Approximation rates for neural networks with encodable weights in smoothness spaces

Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential Equations

(2019) Christian Beck et al.   JOURNAL OF NONLINEAR SCIENCE

Convergence in Orlicz spaces by means of the multivariate max-product neural network operators of the Kantorovich type and applications

(2019) Danilo Costarelli et al.   NEURAL COMPUTING & APPLICATIONS

Smooth Function Approximation by Deep Neural Networks with General Activation Functions

(2019) Ilsang Ohn et al.   Entropy

Error bounds for approximations with deep ReLU neural networks in Ws,p norms

(2019) Ingo Gühring et al.   Analysis and Applications

Deep ReLU networks and high-order finite element methods

(2019) Joost A. A. Opschoor et al.   Analysis and Applications

Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units

(2019) Bo Li   Communications in Computational Physics

Deep learning in high dimension: neural network expression rates for generalized polynomial chaos expansions in UQ

(2018) Christoph Schwab et al.   Analysis and Applications

Provable approximation properties for deep neural networks

(2018) Uri Shaham et al.   APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

DGM: A deep learning algorithm for solving partial differential equations

(2018) Justin Sirignano et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Optimal approximation of piecewise smooth functions using deep ReLU neural networks

(2018) Philipp Petersen et al.   NEURAL NETWORKS

Approximation capability of two hidden layer feedforward neural networks with fixed weights

(2018) Namig J. Guliyev et al.   NEUROCOMPUTING

Solving high-dimensional partial differential equations using deep learning

(2018) Jiequn Han et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Generalization and Expressivity for Deep Nets

(2018) Shao-Bo Lin   IEEE Transactions on Neural Networks and Learning Systems

Error bounds for approximations with deep ReLU networks

(2017) Dmitry Yarotsky   NEURAL NETWORKS

A Single Hidden Layer Feedforward Network with Only One Neuron in the Hidden Layer Can Approximate Any Univariate Function

(2016) Namig J. Guliyev et al.   NEURAL COMPUTATION

Multivariate neural network operators with sigmoidal activation functions

(2013) Danilo Costarelli et al.   NEURAL NETWORKS

Approximation results for neural network operators activated by sigmoidal functions

(2013) Danilo Costarelli et al.   NEURAL NETWORKS