v1v2 (latest)

Optimal approximation of continuous functions by very deep ReLU networks

10 February 2018

Papers citing "Optimal approximation of continuous functions by very deep ReLU networks"

50 / 188 papers shown

Title
Risk bounds for aggregated shallow neural networks using Gaussian prior L. Tinsi A. Dalalyan BDL 78 7 0 21 Dec 2021
Wasserstein Generative Learning of Conditional Distribution Shiao Liu Xingyu Zhou Yuling Jiao Jian Huang GAN 70 21 0 19 Dec 2021
Plant ñ' Seek: Can You Find the Winning Ticket? Jonas Fischer R. Burkholz 81 21 0 22 Nov 2021
On the Existence of Universal Lottery Tickets R. Burkholz Nilanjana Laha Rajarshi Mukherjee Alkis Gotovos UQCV 85 33 0 22 Nov 2021
Deep Network Approximation in Terms of Intrinsic Parameters Zuowei Shen Haizhao Yang Shijun Zhang 64 9 0 15 Nov 2021
$Deep Learning in High Dimension: Neural Network Approximation of Analytic Functions in $L^2(\mathbb{R}^d,γ_d)$$ Deep Learning in High Dimension: Neural Network Approximation of Analytic Functions in $L^2(\mathbb{R}^d,γ_d)$ Christoph Schwab Jakob Zech 28 3 0 13 Nov 2021
A Review of Physics-based Machine Learning in Civil Engineering S. Vadyala S. N. Betgeri J. Matthews Elizabeth Matthews AI4CE 91 157 0 09 Oct 2021
Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows Michael Puthawala Matti Lassas Ivan Dokmanić Maarten V. de Hoop 102 13 0 08 Oct 2021
Robust Nonparametric Regression with Deep Neural Networks Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang OOD 102 13 0 21 Jul 2021
Inverse Problem of Nonlinear Schrödinger Equation as Learning of Convolutional Neural Network Yiran Wang Zhen Li 28 2 0 19 Jul 2021
Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition Guohao Shen Yuling Jiao Yuanyuan Lin J. Horowitz Jian Huang 260 23 0 10 Jul 2021
Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons Zuowei Shen Haizhao Yang Shijun Zhang 183 38 0 06 Jul 2021
Random Neural Networks in the Infinite Width Limit as Gaussian Processes Boris Hanin BDL 100 48 0 04 Jul 2021
On the Representation of Solutions to Elliptic PDEs in Barron Spaces Ziang Chen Jianfeng Lu Yulong Lu 83 29 0 14 Jun 2021
Solving PDEs on Unknown Manifolds with Machine Learning Senwei Liang Shixiao W. Jiang J. Harlim Haizhao Yang AI4CE 114 16 0 12 Jun 2021
Sparsity-Probe: Analysis tool for Deep Learning Models Ido Ben-Shaul S. Dekel 38 4 0 14 May 2021
Non-asymptotic Excess Risk Bounds for Classification with Deep Convolutional Neural Networks Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang 51 3 0 01 May 2021
Automatic Debiased Machine Learning via Riesz Regression Victor Chernozhukov Whitney Newey Victor Quintas-Martinez Vasilis Syrgkanis OOD CML 75 4 0 30 Apr 2021
On the approximation of functions by tanh neural networks Tim De Ryck S. Lanthaler Siddhartha Mishra 76 140 0 18 Apr 2021
Deep Nonparametric Regression on Approximate Manifolds: Non-Asymptotic Error Bounds with Polynomial Prefactors Yuling Jiao Guohao Shen Yuanyuan Lin Jian Huang 125 52 0 14 Apr 2021
Proof of the Theory-to-Practice Gap in Deep Learning via Sampling Complexity bounds for Neural Network Approximation Spaces Philipp Grohs F. Voigtlaender 88 38 0 06 Apr 2021
Approximating Probability Distributions by using Wasserstein Generative Adversarial Networks Yihang Gao Michael K. Ng Mingjie Zhou GAN 39 0 0 18 Mar 2021
Evolutional Deep Neural Network Yifan Du T. Zaki 85 73 0 18 Mar 2021
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth Zuowei Shen Haizhao Yang Shijun Zhang 209 120 0 28 Feb 2021
Size and Depth Separation in Approximating Benign Functions with Neural Networks Gal Vardi Daniel Reichman T. Pitassi Ohad Shamir 103 7 0 30 Jan 2021
On the capacity of deep generative networks for approximating distributions Yunfei Yang Zhen Li Yang Wang 105 30 0 29 Jan 2021
Partition of unity networks: deep hp-approximation Kookjin Lee N. Trask Ravi G. Patel Mamikon A. Gulian E. Cyr 91 30 0 27 Jan 2021
Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification L. Scarabosio 84 9 0 18 Jan 2021
Reproducing Activation Function for Deep Learning Senwei Liang Liyao Lyu Chunmei Wang Haizhao Yang 80 23 0 13 Jan 2021
A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Equations Jianfeng Lu Yulong Lu Min Wang 85 37 0 05 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 114 29 0 11 Dec 2020
Parametric Flatten-T Swish: An Adaptive Non-linear Activation Function For Deep Learning Hock Hung Chieng Noorhaniza Wahid P. Ong 71 6 0 06 Nov 2020
On the rate of convergence of a deep recurrent neural network estimate in a regression problem with dependent data Michael Kohler A. Krzyżak 42 12 0 31 Oct 2020
Learning Sub-Patterns in Piecewise Continuous Functions Anastasis Kratsios Behnoosh Zamanlooy 49 10 0 29 Oct 2020
Deep Learning for Individual Heterogeneity M. Farrell Tengyuan Liang S. Misra BDL 81 0 0 28 Oct 2020
Provable Memorization via Deep Neural Networks using Sub-linear Parameters Sejun Park Jaeho Lee Chulhee Yun Jinwoo Shin FedML MDE 84 37 0 26 Oct 2020
Neural Network Approximation: Three Hidden Layers Are Enough Zuowei Shen Haizhao Yang Shijun Zhang 128 121 0 25 Oct 2020
Exponential ReLU Neural Network Approximation Rates for Point and Edge Singularities C. Marcati J. Opschoor P. Petersen Christoph Schwab 79 30 0 23 Oct 2020
Theoretical Analysis of the Advantage of Deepening Neural Networks Yasushi Esaki Yuta Nakahara Toshiyasu Matsushima 22 0 0 24 Sep 2020
A deep network construction that adapts to intrinsic dimensionality beyond the domain A. Cloninger T. Klock AI4CE 104 14 0 06 Aug 2020
The Kolmogorov-Arnold representation theorem revisited Johannes Schmidt-Hieber 94 147 0 31 Jul 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 97 51 0 09 Jul 2020
Maximum-and-Concatenation Networks Xingyu Xie Hao Kong Jianlong Wu Wayne Zhang Guangcan Liu Zhouchen Lin 157 2 0 09 Jul 2020
Approximation Theory of Tree Tensor Networks: Tensorized Univariate Functions -- Part I Mazen Ali A. Nouy 43 12 0 30 Jun 2020
Deep Network with Approximation Error Being Reciprocal of Width to Power of Square Root of Depth Zuowei Shen Haizhao Yang Shijun Zhang 73 7 0 22 Jun 2020
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth Guy Bresler Dheeraj M. Nagaraj 53 21 0 07 Jun 2020
Approximation in shift-invariant spaces with deep ReLU neural networks Yunfei Yang Zhen Li Yang Wang 76 14 0 25 May 2020
Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks Moritz Geist P. Petersen Mones Raslan R. Schneider Gitta Kutyniok 102 83 0 25 Apr 2020
A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions Yulong Lu Jianfeng Lu 40 19 0 19 Apr 2020
The gap between theory and practice in function approximation with deep neural networks Ben Adcock N. Dexter 73 95 0 16 Jan 2020