Error bounds for approximations with deep ReLU networks

3 October 2016

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

50 / 214 papers shown

Title
Hedonic Prices and Quality Adjusted Price Indices Powered by AI Patrick Bajari Zhihao Cen Victor Chernozhukov Manoj Manukonda Suhas Vijaykumar ... Ramon Huerta Junbo Li Ling Leng George Monokroussos Shan Wan 28 13 0 28 Apr 2023
Performative Prediction with Neural Networks Mehrnaz Mofakhami Ioannis Mitliagkas Gauthier Gidel 40 16 0 14 Apr 2023
Deep neural network approximation of composite functions without the curse of dimensionality Adrian Riekert 26 0 0 12 Apr 2023
Approximation of Nonlinear Functionals Using Deep ReLU Networks Linhao Song Jun Fan Dirong Chen Ding-Xuan Zhou 15 14 0 10 Apr 2023
GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs Yanlai Chen Shawn Koohy PINN AI4CE 37 24 0 27 Mar 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
Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes Christian Haase Christoph Hertrich Georg Loho 34 22 0 24 Feb 2023
Deep Neural Networks for Nonparametric Interaction Models with Diverging Dimension Sohom Bhattacharya Jianqing Fan Debarghya Mukherjee 34 8 0 12 Feb 2023
Learning to Optimize for Reinforcement Learning Qingfeng Lan Rupam Mahmood Shuicheng Yan Zhongwen Xu OffRL 28 6 0 03 Feb 2023
Optimal Approximation Complexity of High-Dimensional Functions with Neural Networks Vincent P. H. Goverse Jad Hamdan Jared Tanner 13 0 0 30 Jan 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
Stretched and measured neural predictions of complex network dynamics V. Vasiliauskaite Nino Antulov-Fantulin 33 1 0 12 Jan 2023
Semiparametric Regression for Spatial Data via Deep Learning Kexuan Li Jun Zhu A. Ives V. Radeloff Fangfang Wang 28 8 0 10 Jan 2023
Statistical guarantees for sparse deep learning Johannes Lederer 19 11 0 11 Dec 2022
Limitations on approximation by deep and shallow neural networks G. Petrova P. Wojtaszczyk 19 7 0 30 Nov 2022
A Law of Data Separation in Deep Learning Hangfeng He Weijie J. Su OOD 24 37 0 31 Oct 2022
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis Luca Galimberti Anastasis Kratsios Giulia Livieri OOD 28 14 0 24 Oct 2022
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective Tanya Marwah Zachary Chase Lipton Jianfeng Lu Andrej Risteski 52 10 0 21 Oct 2022
Towards Global Neural Network Abstractions with Locally-Exact Reconstruction Edoardo Manino I. Bessa Lucas C. Cordeiro 21 1 0 21 Oct 2022
Deep neural network expressivity for optimal stopping problems Lukas Gonon 27 6 0 19 Oct 2022
Approximation analysis of CNNs from a feature extraction view Jianfei Li Han Feng Ding-Xuan Zhou 24 3 0 14 Oct 2022
Analysis of the rate of convergence of an over-parametrized deep neural network estimate learned by gradient descent Michael Kohler A. Krzyżak 32 10 0 04 Oct 2022
Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities S. Lanthaler Roberto Molinaro Patrik Hadorn Siddhartha Mishra 56 24 0 03 Oct 2022
Limitations of neural network training due to numerical instability of backpropagation Clemens Karner V. Kazeev P. Petersen 34 3 0 03 Oct 2022
Parameter-varying neural ordinary differential equations with partition-of-unity networks Kookjin Lee N. Trask 22 2 0 01 Oct 2022
Mega: Moving Average Equipped Gated Attention Xuezhe Ma Chunting Zhou Xiang Kong Junxian He Liangke Gui Graham Neubig Jonathan May Luke Zettlemoyer 33 183 0 21 Sep 2022
Approximation results for Gradient Descent trained Shallow Neural Networks in $1d$ R. Gentile G. Welper ODL 54 6 0 17 Sep 2022
Seeking Interpretability and Explainability in Binary Activated Neural Networks Benjamin Leblanc Pascal Germain FAtt 40 1 0 07 Sep 2022
Solving Elliptic Problems with Singular Sources using Singularity Splitting Deep Ritz Method Tianhao Hu Bangti Jin Zhi Zhou 31 6 0 07 Sep 2022
On the universal consistency of an over-parametrized deep neural network estimate learned by gradient descent Selina Drews Michael Kohler 30 13 0 30 Aug 2022
Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments Mengxin Yu Zhuoran Yang Jianqing Fan OffRL 21 8 0 23 Aug 2022
Shallow neural network representation of polynomials A. Beknazaryan 22 0 0 17 Aug 2022
Optimal Convergence Rates of Deep Neural Networks in a Classification Setting Josephine T. Meyer 27 2 0 25 Jul 2022
Error analysis for deep neural network approximations of parametric hyperbolic conservation laws Tim De Ryck Siddhartha Mishra PINN 15 10 0 15 Jul 2022
Size and depth of monotone neural networks: interpolation and approximation Dan Mikulincer Daniel Reichman 28 7 0 12 Jul 2022
Anisotropic, Sparse and Interpretable Physics-Informed Neural Networks for PDEs A. A. Ramabathiran P. Ramachandran AI4CE 19 0 0 01 Jul 2022
Expressive power of binary and ternary neural networks A. Beknazaryan MQ 19 0 0 27 Jun 2022
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks Daiwei Zhang Tianci Liu Jian Kang BDL UQCV 35 2 0 12 Jun 2022
A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks E. M. Achour Armand Foucault Sébastien Gerchinovitz Franccois Malgouyres 32 7 0 09 Jun 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
Uncertainty quantification of two-phase flow in porous media via coupled-TgNN surrogate model Jun Yu Li Dongxiao Zhang Tianhao He Q. Zheng AI4CE 24 6 0 28 May 2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power Binghui Li Jikai Jin Han Zhong J. Hopcroft Liwei Wang OOD 82 27 0 27 May 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus M. Oprescu CML OOD 35 10 0 23 May 2022
Variable-Input Deep Operator Networks Michael Prasthofer Tim De Ryck Siddhartha Mishra 48 23 0 23 May 2022
Deep Neural Network Classifier for Multi-dimensional Functional Data Shuoyang Wang Guanqun Cao Zuofeng Shang 29 12 0 17 May 2022
On the inability of Gaussian process regression to optimally learn compositional functions M. Giordano Kolyan Ray Johannes Schmidt-Hieber 42 12 0 16 May 2022
Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds Michael O'Connell Guanya Shi Xichen Shi Kamyar Azizzadenesheli Anima Anandkumar Yisong Yue Soon-Jo Chung 75 169 0 13 May 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