Why Shallow Networks Struggle with Approximating and Learning High Frequency: A Numerical Study

29 June 2023

Papers citing "Why Shallow Networks Struggle with Approximating and Learning High Frequency: A Numerical Study"

8 / 8 papers shown

Title
Fourier Multi-Component and Multi-Layer Neural Networks: Unlocking High-Frequency Potential Shijun Zhang Hongkai Zhao Yimin Zhong Haomin Zhou 57 0 0 26 Feb 2025
Orthogonal greedy algorithm for linear operator learning with shallow neural network Ye Lin Jiwei Jia Young Ju Lee Ran Zhang 46 1 0 06 Jan 2025
On the expressiveness and spectral bias of KANs Yixuan Wang Jonathan W. Siegel Ziming Liu Thomas Y. Hou 40 10 0 02 Oct 2024
Structured and Balanced Multi-component and Multi-layer Neural Networks Shijun Zhang Hongkai Zhao Yimin Zhong Haomin Zhou 40 1 0 30 Jun 2024
ReLUs Are Sufficient for Learning Implicit Neural Representations Joseph Shenouda Yamin Zhou Robert D. Nowak 30 5 0 04 Jun 2024
Neural Redshift: Random Networks are not Random Functions Damien Teney A. Nicolicioiu Valentin Hartmann Ehsan Abbasnejad 103 19 0 04 Mar 2024
Deep Network Approximation: Beyond ReLU to Diverse Activation Functions Shijun Zhang Jianfeng Lu Hongkai Zhao 27 17 0 13 Jul 2023
Neural Network Architecture Beyond Width and Depth Zuowei Shen Haizhao Yang Shijun Zhang 3DV MDE 33 13 0 19 May 2022