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ResNet with one-neuron hidden layers is a Universal Approximator

ResNet with one-neuron hidden layers is a Universal Approximator

28 June 2018
Hongzhou Lin
Stefanie Jegelka
ArXivPDFHTML

Papers citing "ResNet with one-neuron hidden layers is a Universal Approximator"

40 / 40 papers shown
Title
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss
T. Getu
Georges Kaddoum
M. Bennis
40
1
0
13 Sep 2023
Are Transformers with One Layer Self-Attention Using Low-Rank Weight
  Matrices Universal Approximators?
Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
T. Kajitsuka
Issei Sato
31
16
0
26 Jul 2023
Universal Approximation Property of Hamiltonian Deep Neural Networks
Universal Approximation Property of Hamiltonian Deep Neural Networks
M. Zakwan
M. d’Angelo
Giancarlo Ferrari-Trecate
36
5
0
21 Mar 2023
Tailor: Altering Skip Connections for Resource-Efficient Inference
Tailor: Altering Skip Connections for Resource-Efficient Inference
Olivia Weng
Gabriel Marcano
Vladimir Loncar
Alireza Khodamoradi
Nojan Sheybani
Andres Meza
F. Koushanfar
K. Denolf
Javier Mauricio Duarte
Ryan Kastner
43
11
0
18 Jan 2023
LU decomposition and Toeplitz decomposition of a neural network
LU decomposition and Toeplitz decomposition of a neural network
Yucong Liu
Simiao Jiao
Lek-Heng Lim
30
7
0
25 Nov 2022
Towards Global Neural Network Abstractions with Locally-Exact
  Reconstruction
Towards Global Neural Network Abstractions with Locally-Exact Reconstruction
Edoardo Manino
I. Bessa
Lucas C. Cordeiro
21
1
0
21 Oct 2022
The (Un)Scalability of Heuristic Approximators for NP-Hard Search
  Problems
The (Un)Scalability of Heuristic Approximators for NP-Hard Search Problems
Sumedh Pendurkar
Taoan Huang
Sven Koenig
Guni Sharon
26
1
0
07 Sep 2022
Approximation of Lipschitz Functions using Deep Spline Neural Networks
Approximation of Lipschitz Functions using Deep Spline Neural Networks
Sebastian Neumayer
Alexis Goujon
Pakshal Bohra
M. Unser
37
16
0
13 Apr 2022
Learning High-Dimensional Parametric Maps via Reduced Basis Adaptive
  Residual Networks
Learning High-Dimensional Parametric Maps via Reduced Basis Adaptive Residual Networks
Thomas O'Leary-Roseberry
Xiaosong Du
A. Chaudhuri
J. Martins
Karen E. Willcox
Omar Ghattas
30
22
0
14 Dec 2021
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series
Daniel Kramer
P. Bommer
Carlo Tombolini
G. Koppe
Daniel Durstewitz
BDL
AI4TS
AI4CE
25
18
0
04 Nov 2021
Neural Flows: Efficient Alternative to Neural ODEs
Neural Flows: Efficient Alternative to Neural ODEs
Marin Bilovs
Johanna Sommer
Syama Sundar Rangapuram
Tim Januschowski
Stephan Günnemann
AI4TS
21
70
0
25 Oct 2021
Meta Internal Learning
Meta Internal Learning
Raphael Bensadoun
Shir Gur
Tomer Galanti
Lior Wolf
GAN
31
8
0
06 Oct 2021
Understanding the computational demands underlying visual reasoning
Understanding the computational demands underlying visual reasoning
Mohit Vaishnav
Rémi Cadène
A. Alamia
Drew Linsley
Rufin VanRullen
Thomas Serre
GNN
CoGe
40
16
0
08 Aug 2021
Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed
  Number of Neurons
Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons
Zuowei Shen
Haizhao Yang
Shijun Zhang
56
36
0
06 Jul 2021
Choose a Transformer: Fourier or Galerkin
Choose a Transformer: Fourier or Galerkin
Shuhao Cao
42
225
0
31 May 2021
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Zuowei Shen
Haizhao Yang
Shijun Zhang
101
115
0
28 Feb 2021
Advances in Electron Microscopy with Deep Learning
Advances in Electron Microscopy with Deep Learning
Jeffrey M. Ede
35
2
0
04 Jan 2021
Convex Potential Flows: Universal Probability Distributions with Optimal
  Transport and Convex Optimization
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang
Ricky T. Q. Chen
Christos Tsirigotis
Aaron Courville
OT
119
95
0
10 Dec 2020
The universal approximation theorem for complex-valued neural networks
The universal approximation theorem for complex-valued neural networks
F. Voigtlaender
27
62
0
06 Dec 2020
Review: Deep Learning in Electron Microscopy
Review: Deep Learning in Electron Microscopy
Jeffrey M. Ede
34
79
0
17 Sep 2020
Expressivity of Deep Neural Networks
Expressivity of Deep Neural Networks
Ingo Gühring
Mones Raslan
Gitta Kutyniok
16
51
0
09 Jul 2020
On Interpretability of Artificial Neural Networks: A Survey
On Interpretability of Artificial Neural Networks: A Survey
Fenglei Fan
Jinjun Xiong
Mengzhou Li
Ge Wang
AAML
AI4CE
38
300
0
08 Jan 2020
Mean-Field and Kinetic Descriptions of Neural Differential Equations
Mean-Field and Kinetic Descriptions of Neural Differential Equations
Michael Herty
T. Trimborn
G. Visconti
36
6
0
07 Jan 2020
Lossless Compression of Deep Neural Networks
Lossless Compression of Deep Neural Networks
Thiago Serra
Abhinav Kumar
Srikumar Ramalingam
24
56
0
01 Jan 2020
Deep Learning via Dynamical Systems: An Approximation Perspective
Deep Learning via Dynamical Systems: An Approximation Perspective
Qianxiao Li
Ting Lin
Zuowei Shen
AI4TS
AI4CE
22
107
0
22 Dec 2019
Are Transformers universal approximators of sequence-to-sequence
  functions?
Are Transformers universal approximators of sequence-to-sequence functions?
Chulhee Yun
Srinadh Bhojanapalli
A. S. Rawat
Sashank J. Reddi
Sanjiv Kumar
8
335
0
20 Dec 2019
Optimal Function Approximation with Relu Neural Networks
Optimal Function Approximation with Relu Neural Networks
Bo Liu
Yi Liang
25
33
0
09 Sep 2019
LassoNet: A Neural Network with Feature Sparsity
LassoNet: A Neural Network with Feature Sparsity
Ismael Lemhadri
Feng Ruan
L. Abraham
Robert Tibshirani
19
121
0
29 Jul 2019
A Review on Deep Learning in Medical Image Reconstruction
A Review on Deep Learning in Medical Image Reconstruction
Hai-Miao Zhang
Bin Dong
MedIm
35
122
0
23 Jun 2019
Universal Approximation with Deep Narrow Networks
Universal Approximation with Deep Narrow Networks
Patrick Kidger
Terry Lyons
34
327
0
21 May 2019
A neural network-based framework for financial model calibration
A neural network-based framework for financial model calibration
Shuaiqiang Liu
Anastasia Borovykh
L. Grzelak
C. Oosterlee
35
103
0
23 Apr 2019
On Residual Networks Learning a Perturbation from Identity
On Residual Networks Learning a Perturbation from Identity
Michael Hauser
24
4
0
11 Feb 2019
On a Sparse Shortcut Topology of Artificial Neural Networks
On a Sparse Shortcut Topology of Artificial Neural Networks
Fenglei Fan
Dayang Wang
Hengtao Guo
Qikui Zhu
Pingkun Yan
Ge Wang
Hengyong Yu
38
22
0
22 Nov 2018
Real-time Power System State Estimation and Forecasting via Deep Neural
  Networks
Real-time Power System State Estimation and Forecasting via Deep Neural Networks
Liang Zhang
G. Wang
G. Giannakis
AI4TS
26
183
0
15 Nov 2018
Empirical Bounds on Linear Regions of Deep Rectifier Networks
Empirical Bounds on Linear Regions of Deep Rectifier Networks
Thiago Serra
Srikumar Ramalingam
8
42
0
08 Oct 2018
Universal Approximation with Quadratic Deep Networks
Universal Approximation with Quadratic Deep Networks
Fenglei Fan
Jinjun Xiong
Ge Wang
PINN
20
78
0
31 Jul 2018
Mad Max: Affine Spline Insights into Deep Learning
Mad Max: Affine Spline Insights into Deep Learning
Randall Balestriero
Richard Baraniuk
AI4CE
31
78
0
17 May 2018
Global optimality conditions for deep neural networks
Global optimality conditions for deep neural networks
Chulhee Yun
S. Sra
Ali Jadbabaie
128
117
0
08 Jul 2017
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
148
602
0
14 Feb 2016
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
183
1,185
0
30 Nov 2014
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