Approximating Continuous Functions by ReLU Nets of Minimal Width

31 October 2017

Papers citing "Approximating Continuous Functions by ReLU Nets of Minimal Width"

49 / 49 papers shown

Title
Non-identifiability distinguishes Neural Networks among Parametric Models Sourav Chatterjee Timothy Sudijono 30 0 0 25 Apr 2025
Explicit neural network classifiers for non-separable data Patrícia Muñoz Ewald 21 0 0 25 Apr 2025
TL-PCA: Transfer Learning of Principal Component Analysis Sharon Hendy Yehuda Dar 161 3 0 14 Oct 2024
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory Guhan Chen Yicheng Li Qian Lin AAML 38 1 0 08 Oct 2024
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks Yunfei Yang 62 2 0 02 Sep 2024
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds Hong Ye Tan Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb 57 0 0 13 Aug 2024
Neural networks in non-metric spaces Luca Galimberti 56 1 0 13 Jun 2024
A Hyper-Transformer model for Controllable Pareto Front Learning with Split Feasibility Constraints Tran Anh Tuan Nguyen Viet Dung Tran Ngoc Thang 39 3 0 04 Feb 2024
Minimum width for universal approximation using ReLU networks on compact domain Namjun Kim Chanho Min Sejun Park VLM 29 10 0 19 Sep 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 32 0 29 Apr 2023
Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes Christian Haase Christoph Hertrich Georg Loho 34 21 0 24 Feb 2023
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions Junyang Cai Khai-Nguyen Nguyen Nishant Shrestha Aidan Good Ruisen Tu Xin Yu Shandian Zhe Thiago Serra MLT 40 7 0 19 Jan 2023
LU decomposition and Toeplitz decomposition of a neural network Yucong Liu Simiao Jiao Lek-Heng Lim 30 7 0 25 Nov 2022
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization Jo Wilton Abigail M. Y. Koay R. Ko Miao Xu N. Ye 21 13 0 16 Oct 2022
Pure Transformers are Powerful Graph Learners Jinwoo Kim Tien Dat Nguyen Seonwoo Min Sungjun Cho Moontae Lee Honglak Lee Seunghoon Hong 43 189 0 06 Jul 2022
Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks Hao Chen Yu Wang Huan Xiong GNN 16 6 0 01 Jun 2022
$Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete$ Training Fully Connected Neural Networks is $\exists\mathbb{R}$ -Complete Daniel Bertschinger Christoph Hertrich Paul Jungeblut Tillmann Miltzow Simon Weber OffRL 59 30 0 04 Apr 2022
Deep Learning for Epidemiologists: An Introduction to Neural Networks S. Serghiou K. Rough FedML 19 13 0 02 Feb 2022
SPINE: Soft Piecewise Interpretable Neural Equations Jasdeep Singh Grover Harsh Minesh Domadia Rajashree Tapase Grishma Sharma 16 0 0 20 Nov 2021
Fourier Neural Networks for Function Approximation R. Subhash K. Yaswanth 22 1 0 21 Oct 2021
Meta Internal Learning Raphael Bensadoun Shir Gur Tomer Galanti Lior Wolf GAN 31 8 0 06 Oct 2021
Densely connected neural networks for nonlinear regression Chao Jiang Canchen Jiang Dongwei Chen Fei Hu PINN 13 20 0 29 Jul 2021
COLD: Concurrent Loads Disaggregator for Non-Intrusive Load Monitoring I. Kamyshev Dmitrii Kriukov E. Gryazina Elena Gryazina Henni Ouerdane 21 8 0 04 Jun 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 32 2 0 04 Jan 2021
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 34 79 0 17 Sep 2020
An Iterative LQR Controller for Off-Road and On-Road Vehicles using a Neural Network Dynamics Model Akhil Nagariya Srikanth Saripalli 19 28 0 28 Jul 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 51 0 09 Jul 2020
Neural Ordinary Differential Equation Control of Dynamics on Graphs Thomas Asikis Lucas Böttcher Nino Antulov-Fantulin 33 43 0 17 Jun 2020
Minimum Width for Universal Approximation Sejun Park Chulhee Yun Jaeho Lee Jinwoo Shin 33 121 0 16 Jun 2020
Approximation in shift-invariant spaces with deep ReLU neural networks Yunfei Yang Zhen Li Yang Wang 34 14 0 25 May 2020
How hard is to distinguish graphs with graph neural networks? Andreas Loukas GNN 25 6 0 13 May 2020
Are Transformers universal approximators of sequence-to-sequence functions? Chulhee Yun Srinadh Bhojanapalli A. S. Rawat Sashank J. Reddi Sanjiv Kumar 6 335 0 20 Dec 2019
Neural Contextual Bandits with UCB-based Exploration Dongruo Zhou Lihong Li Quanquan Gu 36 15 0 11 Nov 2019
On Universal Equivariant Set Networks Nimrod Segol Y. Lipman 3DPC 19 63 0 06 Oct 2019
Optimal Function Approximation with Relu Neural Networks Bo Liu Yi Liang 25 33 0 09 Sep 2019
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 35 122 0 23 Jun 2019
Deep Network Approximation Characterized by Number of Neurons Zuowei Shen Haizhao Yang Shijun Zhang 20 182 0 13 Jun 2019
Universal Approximation with Deep Narrow Networks Patrick Kidger Terry Lyons 29 324 0 21 May 2019
Nonlinear Approximation via Compositions Zuowei Shen Haizhao Yang Shijun Zhang 23 92 0 26 Feb 2019
A Survey of the Recent Architectures of Deep Convolutional Neural Networks Asifullah Khan A. Sohail Umme Zahoora Aqsa Saeed Qureshi OOD 33 2,268 0 17 Jan 2019
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 27 446 0 21 Nov 2018
ResNet with one-neuron hidden layers is a Universal Approximator Hongzhou Lin Stefanie Jegelka 38 227 0 28 Jun 2018
Learning One-hidden-layer ReLU Networks via Gradient Descent Xiao Zhang Yaodong Yu Lingxiao Wang Quanquan Gu MLT 28 134 0 20 Jun 2018
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond Xingguo Li Junwei Lu Zhaoran Wang Jarvis Haupt T. Zhao 27 78 0 13 Jun 2018
Mad Max: Affine Spline Insights into Deep Learning Randall Balestriero Richard Baraniuk AI4CE 31 78 0 17 May 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 15 293 0 10 Feb 2018
The power of deeper networks for expressing natural functions David Rolnick Max Tegmark 31 174 0 16 May 2017
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,746 0 26 Sep 2016
Benefits of depth in neural networks Matus Telgarsky 148 602 0 14 Feb 2016