Minimum Width for Universal Approximation

Minimum Width for Universal Approximation

16 June 2020

Sejun Park

Papers citing "Minimum Width for Universal Approximation"

19 / 19 papers shown

Title
Extended Fiducial Inference for Individual Treatment Effects via Deep Neural Networks Sehwan Kim F. Liang FedML 55 0 0 04 May 2025
TL-PCA: Transfer Learning of Principal Component Analysis Sharon Hendy Yehuda Dar 161 1 0 14 Oct 2024
Robust Weight Initialization for Tanh Neural Networks with Fixed Point Analysis Hyunwoo Lee Hayoung Choi Hyunju Kim 39 1 0 03 Oct 2024
Addressing common misinterpretations of KART and UAT in neural network literature Vugar Ismailov HAI 56 1 0 29 Aug 2024
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds Hong Ye Tan Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb 57 0 0 13 Aug 2024
Statistical Mechanics and Artificial Neural Networks: Principles, Models, and Applications Lucas Böttcher Gregory R. Wheeler 32 0 0 05 Apr 2024
Minimum width for universal approximation using ReLU networks on compact domain Namjun Kim Chanho Min Sejun Park VLM 29 10 0 19 Sep 2023
Data Topology-Dependent Upper Bounds of Neural Network Widths Sangmin Lee Jong Chul Ye 26 0 0 25 May 2023
Development of Non-Linear Equations for Predicting Electrical Conductivity in Silicates P. D. Anjos L. A. Quaresma M. Machado 13 0 0 22 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 32 0 29 Apr 2023
The R-mAtrIx Net Shailesh Lal Suvajit Majumder E. Sobko 24 5 0 14 Apr 2023
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters Wonyeol Lee Sejun Park A. Aiken PINN 13 6 0 31 Jan 2023
LU decomposition and Toeplitz decomposition of a neural network Yucong Liu Simiao Jiao Lek-Heng Lim 30 7 0 25 Nov 2022
Changes from Classical Statistics to Modern Statistics and Data Science Kai Zhang Shan-Yu Liu M. Xiong 31 0 0 30 Oct 2022
Mega: Moving Average Equipped Gated Attention Xuezhe Ma Chunting Zhou Xiang Kong Junxian He Liangke Gui Graham Neubig Jonathan May Luke Zettlemoyer 16 183 0 21 Sep 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 49 20 0 31 Jan 2022
How Attentive are Graph Attention Networks? Shaked Brody Uri Alon Eran Yahav GNN 31 1,016 0 30 May 2021
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 224 1,340 0 12 Feb 2018
Benefits of depth in neural networks Matus Telgarsky 148 602 0 14 Feb 2016