Neural networks and rational functions

11 June 2017

Papers citing "Neural networks and rational functions"

19 / 19 papers shown

Title
Cauchy activation function and XNet Xin Li Zhihong Xia Hongkun Zhang 48 4 0 28 Sep 2024
rKAN: Rational Kolmogorov-Arnold Networks Alireza Afzal Aghaei 47 18 0 20 Jun 2024
A comparison of rational and neural network based approximations V. Peiris R. D. Millán N. Sukhorukova J. Ugon 22 0 0 08 Mar 2023
Learning to Optimize for Reinforcement Learning Qingfeng Lan Rupam Mahmood Shuicheng Yan Zhongwen Xu OffRL 28 6 0 03 Feb 2023
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
On Regularizing Coordinate-MLPs Sameera Ramasinghe L. MacDonald Simon Lucey 158 5 0 01 Feb 2022
Activation Functions in Deep Learning: A Comprehensive Survey and Benchmark S. Dubey S. Singh B. B. Chaudhuri 41 643 0 29 Sep 2021
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks Zhiqian Chen Fanglan Chen Lei Zhang Taoran Ji Kaiqun Fu Liang Zhao Feng Chen Lingfei Wu Charu C. Aggarwal Chang-Tien Lu 53 18 0 21 Jul 2021
Parametric Complexity Bounds for Approximating PDEs with Neural Networks Tanya Marwah Zachary Chase Lipton Andrej Risteski 28 19 0 03 Mar 2021
Consistent Sparse Deep Learning: Theory and Computation Y. Sun Qifan Song F. Liang BDL 43 27 0 25 Feb 2021
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 51 0 09 Jul 2020
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks Alejandro Molina P. Schramowski Kristian Kersting ODL 23 78 0 15 Jul 2019
The phase diagram of approximation rates for deep neural networks Dmitry Yarotsky Anton Zhevnerchuk 24 121 0 22 Jun 2019
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs Gitta Kutyniok P. Petersen Mones Raslan R. Schneider 23 197 0 31 Mar 2019
Theoretical guarantees for sampling and inference in generative models with latent diffusions Belinda Tzen Maxim Raginsky DiffM 17 99 0 05 Mar 2019
On representation power of neural network-based graph embedding and beyond Akifumi Okuno Hidetoshi Shimodaira 21 2 0 31 May 2018
Posterior Concentration for Sparse Deep Learning Nicholas G. Polson Veronika Rockova UQCV BDL 30 88 0 24 Mar 2018
Approximating Continuous Functions by ReLU Nets of Minimal Width Boris Hanin Mark Sellke 44 229 0 31 Oct 2017
Benefits of depth in neural networks Matus Telgarsky 153 603 0 14 Feb 2016