Deep Network Approximation for Smooth Functions

9 January 2020

Papers citing "Deep Network Approximation for Smooth Functions"

50 / 152 papers shown

Title
Super-fast rates of convergence for Neural Networks Classifiers under the Hard Margin Condition Nathanael Tepakbong Ding-Xuan Zhou Xiang Zhou 33 0 0 13 May 2025
Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights Zhaiming Shen Alex Havrilla Rongjie Lai A. Cloninger Wenjing Liao 39 0 0 06 May 2025
Deep learning with missing data Tianyi Ma Tengyao Wang R. Samworth 59 0 0 21 Apr 2025
Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective Yuling Jiao Yanming Lai Yang Wang Bokai Yan 34 0 0 18 Apr 2025
Approximation Bounds for Transformer Networks with Application to Regression Yuling Jiao Yanming Lai Defeng Sun Yang Wang Bokai Yan 29 0 0 16 Apr 2025
Inferring Outcome Means of Exponential Family Distributions Estimated by Deep Neural Networks Xuran Meng Yi Li BDL 25 0 0 12 Apr 2025
Statistically guided deep learning Michael Kohler A. Krzyżak ODL BDL 68 0 0 11 Apr 2025
Nonlocal techniques for the analysis of deep ReLU neural network approximations Cornelia Schneider Mario Ullrich Jan Vybiral 18 0 0 07 Apr 2025
Approximation properties of neural ODEs Arturo De Marinis Davide Murari E. Celledoni Nicola Guglielmi B. Owren Francesco Tudisco 39 0 0 19 Mar 2025
Finite Samples for Shallow Neural Networks Yu Xia Zhiqiang Xu 43 0 0 17 Mar 2025
Fourier Multi-Component and Multi-Layer Neural Networks: Unlocking High-Frequency Potential Shijun Zhang Hongkai Zhao Yimin Zhong Haomin Zhou 52 0 0 26 Feb 2025
Curse of Dimensionality in Neural Network Optimization Sanghoon Na Haizhao Yang 51 0 0 07 Feb 2025
Learning with Noisy Labels: the Exploration of Error Bounds in Classification Haixia Liu Boxiao Li Can Yang Yang Wang 33 0 0 28 Jan 2025
Higher Order Approximation Rates for ReLU CNNs in Korobov Spaces Yuwen Li Guozhi Zhang 43 1 0 20 Jan 2025
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning Yihong Gu Cong Fang Peter Bühlmann Jianqing Fan CML OOD 70 2 0 31 Dec 2024
Deep Kalman Filters Can Filter Blanka Hovart Anastasis Kratsios Yannick Limmer Xuwei Yang 45 1 0 31 Dec 2024
A Statistical Analysis of Deep Federated Learning for Intrinsically Low-dimensional Data Saptarshi Chakraborty Peter L. Bartlett FedML 18 1 0 28 Oct 2024
Simultaneously Solving FBSDEs with Neural Operators of Logarithmic Depth, Constant Width, and Sub-Linear Rank Takashi Furuya Anastasis Kratsios 30 1 0 18 Oct 2024
On the expressiveness and spectral bias of KANs Yixuan Wang Jonathan W. Siegel Ziming Liu Thomas Y. Hou 37 9 0 02 Oct 2024
Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study Hao Liu Zecheng Zhang Wenjing Liao Hayden Schaeffer 23 1 0 01 Oct 2024
Frequency-adaptive Multi-scale Deep Neural Networks Jizu Huang Rukang You Tao Zhou AI4CE 25 1 0 28 Sep 2024
Approximation Bounds for Recurrent Neural Networks with Application to Regression Yuling Jiao Yang Wang Bokai Yan 23 1 0 09 Sep 2024
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks Yunfei Yang 59 2 0 02 Sep 2024
Time Series Generative Learning with Application to Brain Imaging Analysis Zhenghao Li Sanyou Wu Long Feng MedIm 33 0 0 19 Jul 2024
Theoretical Insights into CycleGAN: Analyzing Approximation and Estimation Errors in Unpaired Data Generation Luwei Sun Dongrui Shen Han Feng 29 2 0 16 Jul 2024
Structured and Balanced Multi-component and Multi-layer Neural Networks Shijun Zhang Hongkai Zhao Yimin Zhong Haomin Zhou 32 1 0 30 Jun 2024
On the growth of the parameters of approximating ReLU neural networks Erion Morina Martin Holler 25 0 0 21 Jun 2024
On the estimation rate of Bayesian PINN for inverse problems Yi Sun Debarghya Mukherjee Yves Atchadé PINN 72 1 0 21 Jun 2024
Posterior and variational inference for deep neural networks with heavy-tailed weights Ismael Castillo Paul Egels BDL 55 3 0 05 Jun 2024
On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes Zhiheng Chen Guanhua Fang Wen Yu 30 0 0 02 Jun 2024
Sifting through the Noise: A Survey of Diffusion Probabilistic Models and Their Applications to Biomolecules Trevor Norton Debswapna Bhattacharya MedIm DiffM 47 2 0 31 May 2024
Enhancing Accuracy in Generative Models via Knowledge Transfer Xinyu Tian Xiaotong Shen 39 2 0 27 May 2024
Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations Chuqi Chen Yahong Yang Yang Xiang Wenrui Hao 26 2 0 23 May 2024
Model Free Prediction with Uncertainty Assessment Yuling Jiao Lican Kang Jin Liu Heng Peng Heng Zuo DiffM 34 0 0 21 May 2024
Approximation and Gradient Descent Training with Neural Networks G. Welper 36 1 0 19 May 2024
Mixture of Experts Soften the Curse of Dimensionality in Operator Learning Anastasis Kratsios Takashi Furuya Jose Antonio Lara Benitez Matti Lassas Maarten V. de Hoop 42 13 0 13 Apr 2024
An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization Minshuo Chen Song Mei Jianqing Fan Mengdi Wang VLM MedIm DiffM 37 48 0 11 Apr 2024
Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 37 4 0 04 Apr 2024
On the rates of convergence for learning with convolutional neural networks Yunfei Yang Han Feng Ding-Xuan Zhou 40 3 0 25 Mar 2024
Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning Farhad Pourkamali-Anaraki Jamal F. Husseini Scott E. Stapleton UD 48 2 0 21 Feb 2024
Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts Anastasis Kratsios Haitz Sáez de Ocáriz Borde Takashi Furuya Marc T. Law MoE 41 1 0 05 Feb 2024
Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss Yahong Yang Juncai He AI4CE 26 7 0 31 Jan 2024
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning Hao Liu Biraj Dahal Rongjie Lai Wenjing Liao AI4CE 26 5 0 19 Jan 2024
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models Namjoon Suh Guang Cheng MedIm 22 12 0 14 Jan 2024
Semi-Supervised Deep Sobolev Regression: Estimation and Variable Selection by ReQU Neural Network Zhao Ding Chenguang Duan Yuling Jiao Jerry Zhijian Yang 25 1 0 09 Jan 2024
Deep Neural Networks and Finite Elements of Any Order on Arbitrary Dimensions Juncai He Jinchao Xu 25 7 0 21 Dec 2023
Neural Network Approximation for Pessimistic Offline Reinforcement Learning Di Wu Yuling Jiao Li Shen Haizhao Yang Xiliang Lu OffRL 27 1 0 19 Dec 2023
Optimal Deep Neural Network Approximation for Korobov Functions with respect to Sobolev Norms Yahong Yang Yulong Lu 34 3 0 08 Nov 2023
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries Haitz Sáez de Ocáriz Borde Anastasis Kratsios 37 4 0 23 Oct 2023
On Representation Complexity of Model-based and Model-free Reinforcement Learning Hanlin Zhu Baihe Huang Stuart Russell OffRL 25 3 0 03 Oct 2023