Deep Network Approximation Characterized by Number of Neurons

13 June 2019

Papers citing "Deep Network Approximation Characterized by Number of Neurons"

40 / 40 papers shown

Title
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Jialong Jiang Wenkang Hu Jian Huang Yuling Jiao Xu Liu DiffM 50 0 0 08 May 2025
Learning with Noisy Labels: the Exploration of Error Bounds in Classification Haixia Liu Boxiao Li Can Yang Yang Wang 41 0 0 28 Jan 2025
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks Yunfei Yang 62 2 0 02 Sep 2024
Time Series Generative Learning with Application to Brain Imaging Analysis Zhenghao Li Sanyou Wu Long Feng MedIm 41 0 0 19 Jul 2024
Generative adversarial learning with optimal input dimension and its adaptive generator architecture Zhiyao Tan Ling Zhou Huazhen Lin GAN 42 0 0 06 May 2024
Double-well Net for Image Segmentation Haotian Liu Jun Liu Raymond H. F. Chan Xue-Cheng Tai 47 7 0 31 Dec 2023
Expressivity and Approximation Properties of Deep Neural Networks with ReLU $^k$ Activation Juncai He Tong Mao Jinchao Xu 37 3 0 27 Dec 2023
Neural Network Approximation for Pessimistic Offline Reinforcement Learning Di Wu Yuling Jiao Li Shen Haizhao Yang Xiliang Lu OffRL 29 1 0 19 Dec 2023
Multi-Grade Deep Learning for Partial Differential Equations with Applications to the Burgers Equation Yuesheng Xu Taishan Zeng AI4CE 32 4 0 14 Sep 2023
Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives Yahong Yang Haizhao Yang Yang Xiang 31 19 0 15 May 2023
Deep neural network approximation of composite functions without the curse of dimensionality Adrian Riekert 24 0 0 12 Apr 2023
Deep Nonparametric Estimation of Intrinsic Data Structures by Chart Autoencoders: Generalization Error and Robustness Hao Liu Alex Havrilla Rongjie Lai Wenjing Liao 39 6 0 17 Mar 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 59 8 0 11 Mar 2023
Error convergence and engineering-guided hyperparameter search of PINNs: towards optimized I-FENN performance Panos Pantidis Habiba Eldababy Christopher Miguel Tagle M. Mobasher 35 20 0 03 Mar 2023
Approximation analysis of CNNs from a feature extraction view Jianfei Li Han Feng Ding-Xuan Zhou 24 3 0 14 Oct 2022
Deep Neural Network Approximation of Invariant Functions through Dynamical Systems Qianxiao Li T. Lin Zuowei Shen 24 6 0 18 Aug 2022
Deep Sufficient Representation Learning via Mutual Information Siming Zheng Yuanyuan Lin Jian Huang SSL DRL 47 0 0 21 Jul 2022
Convergence of Deep Neural Networks with General Activation Functions and Pooling Wentao Huang Yuesheng Xu Haizhang Zhang MLT AI4CE 23 0 0 13 May 2022
How do noise tails impact on deep ReLU networks? Jianqing Fan Yihong Gu Wen-Xin Zhou ODL 38 13 0 20 Mar 2022
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces Hao Liu Haizhao Yang Minshuo Chen T. Zhao Wenjing Liao 32 36 0 01 Jan 2022
A Deep Generative Approach to Conditional Sampling Xingyu Zhou Yuling Jiao Jin Liu Jian Huang 10 41 0 19 Oct 2021
Convergence of Deep Convolutional Neural Networks Yuesheng Xu Haizhang Zhang MLT 40 44 0 28 Sep 2021
Convergence of Deep ReLU Networks Yuesheng Xu Haizhang Zhang 37 26 0 27 Jul 2021
Robust Nonparametric Regression with Deep Neural Networks Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang OOD 33 13 0 21 Jul 2021
Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons Zuowei Shen Haizhao Yang Shijun Zhang 56 36 0 06 Jul 2021
Deep Generative Learning via Schrödinger Bridge Gefei Wang Yuling Jiao Qiang Xu Yang Wang Can Yang DiffM OT 23 92 0 19 Jun 2021
The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation Q. Du Yiqi Gu Haizhao Yang Chao Zhou 26 20 0 21 Mar 2021
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth Zuowei Shen Haizhao Yang Shijun Zhang 103 115 0 28 Feb 2021
Size and Depth Separation in Approximating Benign Functions with Neural Networks Gal Vardi Daniel Reichman T. Pitassi Ohad Shamir 28 7 0 30 Jan 2021
Reproducing Activation Function for Deep Learning Senwei Liang Liyao Lyu Chunmei Wang Haizhao Yang 36 21 0 13 Jan 2021
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 36 29 0 11 Dec 2020
Neural Network Approximation: Three Hidden Layers Are Enough Zuowei Shen Haizhao Yang Shijun Zhang 30 115 0 25 Oct 2020
Stochastic Markov Gradient Descent and Training Low-Bit Neural Networks Jonathan Ashbrock A. Powell MQ 28 5 0 25 Aug 2020
The Kolmogorov-Arnold representation theorem revisited Johannes Schmidt-Hieber 30 125 0 31 Jul 2020
Two-Layer Neural Networks for Partial Differential Equations: Optimization and Generalization Theory Tao Luo Haizhao Yang 32 73 0 28 Jun 2020
Approximation in shift-invariant spaces with deep ReLU neural networks Yunfei Yang Zhen Li Yang Wang 34 14 0 25 May 2020
Overall error analysis for the training of deep neural networks via stochastic gradient descent with random initialisation Arnulf Jentzen Timo Welti 17 15 0 03 Mar 2020
Deep Network Approximation for Smooth Functions Jianfeng Lu Zuowei Shen Haizhao Yang Shijun Zhang 67 247 0 09 Jan 2020
Deep Learning via Dynamical Systems: An Approximation Perspective Qianxiao Li Ting Lin Zuowei Shen AI4TS AI4CE 22 107 0 22 Dec 2019
Nonlinear Approximation and (Deep) ReLU Networks Ingrid Daubechies Ronald A. DeVore S. Foucart Boris Hanin G. Petrova 22 138 0 05 May 2019