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Error bounds for approximations with deep ReLU networks
v1v2v3 (latest)

Error bounds for approximations with deep ReLU networks

3 October 2016
Dmitry Yarotsky
ArXiv (abs)PDFHTML

Papers citing "Error bounds for approximations with deep ReLU networks"

50 / 633 papers shown
New universal operator approximation theorem for encoder-decoder architectures (Preprint)
New universal operator approximation theorem for encoder-decoder architectures (Preprint)
Janek Gödeke
Pascal Fernsel
215
1
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31 Mar 2025
An extension of linear self-attention for in-context learning
An extension of linear self-attention for in-context learning
Katsuyuki Hagiwara
245
0
0
31 Mar 2025
Feature Qualification by Deep Nets: A Constructive Approach
Feature Qualification by Deep Nets: A Constructive Approach
Feilong Cao
Shao-Bo Lin
MLT
180
0
0
24 Mar 2025
Theory-to-Practice Gap for Neural Networks and Neural Operators
Theory-to-Practice Gap for Neural Networks and Neural Operators
Philipp Grohs
S. Lanthaler
Margaret Trautner
278
4
0
23 Mar 2025
Approximation properties of neural ODEs
Approximation properties of neural ODEs
Arturo De Marinis
Davide Murari
E. Celledoni
Nicola Guglielmi
B. Owren
Francesco Tudisco
247
3
0
19 Mar 2025
Self-Consistent Equation-guided Neural Networks for Censored Time-to-Event Data
Sehwan Kim
Rui Wang
Wenbin Lu
196
0
0
13 Mar 2025
Numerical and statistical analysis of NeuralODE with Runge-Kutta time integration
Emily C. Ehrhardt
Hanno Gottschalk
Tobias Riedlinger
219
1
0
13 Mar 2025
Fourier Multi-Component and Multi-Layer Neural Networks: Unlocking High-Frequency Potential
Fourier Multi-Component and Multi-Layer Neural Networks: Unlocking High-Frequency Potential
Shijun Zhang
Hongkai Zhao
Yimin Zhong
Haomin Zhou
324
1
0
26 Feb 2025
Curse of Dimensionality in Neural Network Optimization
Curse of Dimensionality in Neural Network Optimization
Sanghoon Na
Haizhao Yang
343
0
0
07 Feb 2025
Higher Order Approximation Rates for ReLU CNNs in Korobov Spaces
Higher Order Approximation Rates for ReLU CNNs in Korobov Spaces
Yuwen Li
Guozhi Zhang
359
2
0
20 Jan 2025
Deep Partially Linear Transformation Model for Right-Censored Survival Data
Deep Partially Linear Transformation Model for Right-Censored Survival Data
Junkai Yin
Yue Zhang
Zhangsheng Yu
477
1
0
10 Dec 2024
Can neural operators always be continuously discretized?
Can neural operators always be continuously discretized?Neural Information Processing Systems (NeurIPS), 2024
Takashi Furuya
Michael Puthawala
Maarten V. de Hoop
Matti Lassas
290
1
0
04 Dec 2024
Theoretical limitations of multi-layer Transformer
Theoretical limitations of multi-layer Transformer
Lijie Chen
Binghui Peng
Hongxun Wu
AI4CE
480
23
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04 Dec 2024
A Data-Driven Modeling and Motion Control of Heavy-Load Hydraulic
  Manipulators via Reversible Transformation
A Data-Driven Modeling and Motion Control of Heavy-Load Hydraulic Manipulators via Reversible Transformation
Dexian Ma
Y. Liu
Wenbo Liu
Bo Zhou
AI4CE
142
1
0
21 Nov 2024
Understanding Scaling Laws with Statistical and Approximation Theory for
  Transformer Neural Networks on Intrinsically Low-dimensional Data
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional DataNeural Information Processing Systems (NeurIPS), 2024
Alex Havrilla
Wenjing Liao
262
20
0
11 Nov 2024
Gradient Descent Finds Over-Parameterized Neural Networks with Sharp Generalization for Nonparametric Regression
Gradient Descent Finds Over-Parameterized Neural Networks with Sharp Generalization for Nonparametric Regression
Yingzhen Yang
Ping Li
MLT
598
1
0
05 Nov 2024
When can classical neural networks represent quantum states?
When can classical neural networks represent quantum states?
Tai-Hsuan Yang
Mehdi Soleimanifar
Thiago Bergamaschi
J. Preskill
227
19
0
30 Oct 2024
Computable Lipschitz Bounds for Deep Neural Networks
Computable Lipschitz Bounds for Deep Neural Networks
Moreno Pintore
Bruno Després
354
1
0
28 Oct 2024
LAMA: Stable Dual-Domain Deep Reconstruction For Sparse-View CT
LAMA: Stable Dual-Domain Deep Reconstruction For Sparse-View CTJournal of Mathematical Imaging and Vision (JMIV), 2024
Chi-Jiao Ding
Qingchao Zhang
Ge Wang
X. Ye
Yunmei Chen
202
0
0
28 Oct 2024
A Statistical Analysis of Deep Federated Learning for Intrinsically Low-dimensional Data
A Statistical Analysis of Deep Federated Learning for Intrinsically Low-dimensional Data
Saptarshi Chakraborty
Peter L. Bartlett
FedML
352
1
0
28 Oct 2024
Representation-Enhanced Neural Knowledge Integration with Application to
  Large-Scale Medical Ontology Learning
Representation-Enhanced Neural Knowledge Integration with Application to Large-Scale Medical Ontology Learning
Suqi Liu
Tianxi Cai
Xiaoou Li
218
2
0
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CAPEEN: Image Captioning with Early Exits and Knowledge Distillation
CAPEEN: Image Captioning with Early Exits and Knowledge DistillationConference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Divya J. Bajpai
M. Hanawal
VLM
213
10
0
06 Oct 2024
Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed
  Neural Networks
Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed Neural Networks
Tianchi Yu
Jingwei Qiu
Jiang Yang
Ivan Oseledets
195
4
0
05 Oct 2024
Robust Weight Initialization for Tanh Neural Networks with Fixed Point Analysis
Robust Weight Initialization for Tanh Neural Networks with Fixed Point AnalysisInternational Conference on Learning Representations (ICLR), 2024
Hyunwoo Lee
Hayoung Choi
Hyunju Kim
210
5
0
03 Oct 2024
On the expressiveness and spectral bias of KANs
On the expressiveness and spectral bias of KANsInternational Conference on Learning Representations (ICLR), 2024
Yixuan Wang
Jonathan W. Siegel
Ziming Liu
Thomas Y. Hou
402
40
0
02 Oct 2024
A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
Shivam Kumar
Yun Yang
Lizhen Lin
266
1
0
02 Oct 2024
Structure-Preserving Operator Learning
Structure-Preserving Operator Learning
Nacime Bouziani
Nicolas Boullé
209
4
0
01 Oct 2024
Neural Scaling Laws of Deep ReLU and Deep Operator Network: A
  Theoretical Study
Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study
Hao Liu
Zecheng Zhang
Wenjing Liao
Hayden Schaeffer
329
6
0
01 Oct 2024
Cauchy activation function and XNet
Cauchy activation function and XNetNeural Networks (NN), 2024
Xin Li
Zhihong Xia
Hongkun Zhang
381
9
0
28 Sep 2024
On the Power of Decision Trees in Auto-Regressive Language Modeling
On the Power of Decision Trees in Auto-Regressive Language ModelingNeural Information Processing Systems (NeurIPS), 2024
Yulu Gan
Tomer Galanti
T. Poggio
Eran Malach
AI4CE
130
1
0
27 Sep 2024
Component-based Sketching for Deep ReLU Nets
Component-based Sketching for Deep ReLU Nets
Di Wang
Shao-Bo Lin
Deyu Meng
Feilong Cao
176
1
0
21 Sep 2024
Approximation Bounds for Recurrent Neural Networks with Application to Regression
Approximation Bounds for Recurrent Neural Networks with Application to Regression
Yuling Jiao
Yang Wang
Bokai Yan
256
1
0
09 Sep 2024
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networksApplied and Computational Harmonic Analysis (ACHA), 2024
Yunfei Yang
396
5
0
02 Sep 2024
A Statistical Framework for Data-dependent Retrieval-Augmented Models
A Statistical Framework for Data-dependent Retrieval-Augmented ModelsInternational Conference on Machine Learning (ICML), 2024
Soumya Basu
A. S. Rawat
Manzil Zaheer
RALM
283
2
0
27 Aug 2024
Transformers are Minimax Optimal Nonparametric In-Context Learners
Transformers are Minimax Optimal Nonparametric In-Context LearnersNeural Information Processing Systems (NeurIPS), 2024
Juno Kim
Tai Nakamaki
Taiji Suzuki
334
28
0
22 Aug 2024
Multilevel CNNs for Parametric PDEs based on Adaptive Finite Elements
Multilevel CNNs for Parametric PDEs based on Adaptive Finite Elements
Janina Enrica Schutte
Martin Eigel
AI4CE
193
1
0
20 Aug 2024
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds
Hong Ye Tan
Subhadip Mukherjee
Junqi Tang
Carola-Bibiane Schönlieb
321
0
0
13 Aug 2024
Convergence Analysis for Deep Sparse Coding via Convolutional Neural Networks
Convergence Analysis for Deep Sparse Coding via Convolutional Neural Networks
Jianfei Li
Han Feng
Ding-Xuan Zhou
329
3
0
10 Aug 2024
Transformers are Universal In-context Learners
Transformers are Universal In-context LearnersInternational Conference on Learning Representations (ICLR), 2024
Takashi Furuya
Maarten V. de Hoop
Gabriel Peyré
292
22
0
02 Aug 2024
Causal Deepsets for Off-policy Evaluation under Spatial or
  Spatio-temporal Interferences
Causal Deepsets for Off-policy Evaluation under Spatial or Spatio-temporal Interferences
Runpeng Dai
Jianing Wang
Fan Zhou
Shuang Luo
Zhiwei Qin
Chengchun Shi
Hongtu Zhu
CMLOffRL
218
2
0
25 Jul 2024
Time Series Generative Learning with Application to Brain Imaging
  Analysis
Time Series Generative Learning with Application to Brain Imaging Analysis
Zhenghao Li
Sanyou Wu
Long Feng
MedIm
227
0
0
19 Jul 2024
Theoretical Insights into CycleGAN: Analyzing Approximation and Estimation Errors in Unpaired Data Generation
Theoretical Insights into CycleGAN: Analyzing Approximation and Estimation Errors in Unpaired Data Generation
Luwei Sun
Dongrui Shen
Han Feng
428
4
0
16 Jul 2024
Causal inference through multi-stage learning and doubly robust deep
  neural networks
Causal inference through multi-stage learning and doubly robust deep neural networks
Yuqian Zhang
Jelena Bradic
OODCML
244
2
0
11 Jul 2024
Stochastic Gradient Descent for Two-layer Neural Networks
Stochastic Gradient Descent for Two-layer Neural Networks
Dinghao Cao
Zheng-Chu Guo
Lei Shi
MLT
229
1
0
10 Jul 2024
Equidistribution-based training of Free Knot Splines and ReLU Neural Networks
Equidistribution-based training of Free Knot Splines and ReLU Neural Networks
Simone Appella
S. Arridge
Chris Budd
Teo Deveney
L. Kreusser
232
1
0
02 Jul 2024
Neural Networks Trained by Weight Permutation are Universal Approximators
Neural Networks Trained by Weight Permutation are Universal Approximators
Yongqiang Cai
Gaohang Chen
Zhonghua Qiao
537
2
0
01 Jul 2024
Structured and Balanced Multi-Component and Multi-Layer Neural Networks
Structured and Balanced Multi-Component and Multi-Layer Neural Networks
Shijun Zhang
Hongkai Zhao
Yimin Zhong
Haomin Zhou
380
6
0
30 Jun 2024
BrowNNe: Brownian Nonlocal Neurons & Activation Functions
BrowNNe: Brownian Nonlocal Neurons & Activation Functions
Sriram Nagaraj
Truman Hickok
151
0
0
21 Jun 2024
On the estimation rate of Bayesian PINN for inverse problems
On the estimation rate of Bayesian PINN for inverse problems
Yi Sun
Debarghya Mukherjee
Yves Atchadé
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291
1
0
21 Jun 2024
GraphKAN: Enhancing Feature Extraction with Graph Kolmogorov Arnold
  Networks
GraphKAN: Enhancing Feature Extraction with Graph Kolmogorov Arnold Networks
Fan Zhang
Xin Zhang
325
46
0
19 Jun 2024
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