Deep Network Approximation for Smooth Functions

9 January 2020

Papers citing "Deep Network Approximation for Smooth Functions"

50 / 152 papers shown

Title
Solving Two-Player General-Sum Games Between Swarms Mukesh Ghimire Lei Zhang Wenlong Zhang Yi Ren Zhenni Xu 24 1 0 02 Oct 2023
Spectral Neural Networks: Approximation Theory and Optimization Landscape Chenghui Li Rishi Sonthalia Nicolas García Trillos 27 1 0 01 Oct 2023
Approximation Results for Gradient Descent trained Neural Networks G. Welper 48 0 0 09 Sep 2023
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models Changyu Liu Yuling Jiao Junhui Wang Jian Huang AAML 17 2 0 02 Sep 2023
On the Optimal Expressive Power of ReLU DNNs and Its Application in Approximation with Kolmogorov Superposition Theorem Juncai He 13 10 0 10 Aug 2023
Optimal Approximation and Learning Rates for Deep Convolutional Neural Networks Shao-Bo Lin 16 1 0 07 Aug 2023
Weighted variation spaces and approximation by shallow ReLU networks Ronald A. DeVore Robert D. Nowak Rahul Parhi Jonathan W. Siegel 26 5 0 28 Jul 2023
Connections between Operator-splitting Methods and Deep Neural Networks with Applications in Image Segmentation Hao Liu X. Tai Raymond H. F. Chan 20 3 0 18 Jul 2023
Deep Network Approximation: Beyond ReLU to Diverse Activation Functions Shijun Zhang Jianfeng Lu Hongkai Zhao 11 17 0 13 Jul 2023
Sup-Norm Convergence of Deep Neural Network Estimator for Nonparametric Regression by Adversarial Training Masaaki Imaizumi AAML 13 4 0 08 Jul 2023
Learning Theory of Distribution Regression with Neural Networks Zhongjie Shi Zhan Yu Ding-Xuan Zhou 11 2 0 07 Jul 2023
Why Shallow Networks Struggle with Approximating and Learning High Frequency: A Numerical Study Shijun Zhang Hongkai Zhao Yimin Zhong Haomin Zhou 21 7 0 29 Jun 2023
UTOPIA: Universally Trainable Optimal Prediction Intervals Aggregation Jianqing Fan Jiawei Ge Debarghya Mukherjee AI4TS 23 6 0 28 Jun 2023
Exploring the Complexity of Deep Neural Networks through Functional Equivalence Guohao Shen 22 2 0 19 May 2023
Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives Yahong Yang Haizhao Yang Yang Xiang 29 19 0 15 May 2023
Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang 48 3 0 01 May 2023
Deep neural network approximation of composite functions without the curse of dimensionality Adrian Riekert 22 0 0 12 Apr 2023
Optimal rates of approximation by shallow ReLU $^k$ neural networks and applications to nonparametric regression Yunfei Yang Ding-Xuan Zhou 34 19 0 04 Apr 2023
One Neuron Saved Is One Neuron Earned: On Parametric Efficiency of Quadratic Networks Fenglei Fan Hangcheng Dong Zhongming Wu Lecheng Ruan T. Zeng Yiming Cui Jing-Xiao Liao 54 8 0 11 Mar 2023
Deep Neural Networks for Nonparametric Interaction Models with Diverging Dimension Sohom Bhattacharya Jianqing Fan Debarghya Mukherjee 28 8 0 12 Feb 2023
Sharp Lower Bounds on Interpolation by Deep ReLU Neural Networks at Irregularly Spaced Data Jonathan W. Siegel 6 2 0 02 Feb 2023
On Enhancing Expressive Power via Compositions of Single Fixed-Size ReLU Network Shijun Zhang Jianfeng Lu Hongkai Zhao CoGe 23 4 0 29 Jan 2023
Deep Operator Learning Lessens the Curse of Dimensionality for PDEs Ke Chen Chunmei Wang Haizhao Yang AI4CE 16 13 0 28 Jan 2023
Semiparametric Regression for Spatial Data via Deep Learning Kexuan Li Jun Zhu A. Ives V. Radeloff Fangfang Wang 20 8 0 10 Jan 2023
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 20 34 0 06 Dec 2022
On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds Ming Jin Vanshaj Khattar Harshal D. Kaushik Bilgehan Sel R. Jia 13 8 0 02 Dec 2022
Limitations on approximation by deep and shallow neural networks G. Petrova P. Wojtaszczyk 11 7 0 30 Nov 2022
Optimal Approximation Rates for Deep ReLU Neural Networks on Sobolev and Besov Spaces Jonathan W. Siegel 20 28 0 25 Nov 2022
On the Universal Approximation Property of Deep Fully Convolutional Neural Networks Ting-Wei Lin Zuowei Shen Qianxiao Li 26 4 0 25 Nov 2022
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis Luca Galimberti Anastasis Kratsios Giulia Livieri OOD 28 14 0 24 Oct 2022
SignReLU neural network and its approximation ability Jianfei Li Han Feng Ding-Xuan Zhou 17 3 0 19 Oct 2022
Active Learning with Neural Networks: Insights from Nonparametric Statistics Yinglun Zhu Robert D. Nowak 72 6 0 15 Oct 2022
DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning Siqi Xu Lin Liu Zhong Liu CML MedIm 26 8 0 10 Oct 2022
Factor Augmented Sparse Throughput Deep ReLU Neural Networks for High Dimensional Regression Jianqing Fan Yihong Gu 14 21 0 05 Oct 2022
Analysis of the rate of convergence of an over-parametrized deep neural network estimate learned by gradient descent Michael Kohler A. Krzyżak 32 10 0 04 Oct 2022
Approximation results for Gradient Descent trained Shallow Neural Networks in $1d$ R. Gentile G. Welper ODL 46 6 0 17 Sep 2022
A variational neural network approach for glacier modelling with nonlinear rheology Tiangang Cui Zhongjian Wang Zhiwen Zhang 24 4 0 05 Sep 2022
On the universal consistency of an over-parametrized deep neural network estimate learned by gradient descent Selina Drews Michael Kohler 25 13 0 30 Aug 2022
CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning Ben Adcock Juan M. Cardenas N. Dexter 27 8 0 25 Aug 2022
Deep Neural Network Approximation of Invariant Functions through Dynamical Systems Qianxiao Li T. Lin Zuowei Shen 21 6 0 18 Aug 2022
The BUTTER Zone: An Empirical Study of Training Dynamics in Fully Connected Neural Networks Charles Edison Tripp J. Perr-Sauer L. Hayne M. Lunacek Jamil Gafur AI4CE 21 0 0 25 Jul 2022
Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks Guohao Shen Yuling Jiao Yuanyuan Lin J. Horowitz Jian Huang 17 4 0 21 Jul 2022
Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary Tianyang Hu Ruiqi Liu Zuofeng Shang Guang Cheng 22 3 0 04 Jul 2022
Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations Denis Belomestny A. Naumov Nikita Puchkin S. Samsonov 11 21 0 20 Jun 2022
Neural Network Architecture Beyond Width and Depth Zuowei Shen Haizhao Yang Shijun Zhang 3DV MDE 31 13 0 19 May 2022
A scalable deep learning approach for solving high-dimensional dynamic optimal transport Wei Wan Yuejin Zhang Chenglong Bao Bin Dong Zuoqiang Shi 8 4 0 16 May 2022
Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions? Anastasis Kratsios Behnoosh Zamanlooy MLT 62 3 0 24 Apr 2022
How do noise tails impact on deep ReLU networks? Jianqing Fan Yihong Gu Wen-Xin Zhou ODL 38 13 0 20 Mar 2022
IAE-Net: Integral Autoencoders for Discretization-Invariant Learning Yong Zheng Ong Zuowei Shen Haizhao Yang 11 15 0 10 Mar 2022
A Note on Machine Learning Approach for Computational Imaging Bin Dong 17 0 0 24 Feb 2022