Fetching the paper…
Reading the bibliography…
Frequency perspective recently makes progress in understanding deep learning.
Frequency principle: Fourier analysis sheds light on deep neural networks
Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo, Yanyang Xiao, and Zheng Ma · 1901
Earlier work this paper cites.
An efficient method for finding the minimum of a function of several variables without calculating derivatives
Michael JD Powell · 1964
Earlier work this paper cites.
Preconditioning of truncated-newton methods
Stephen G Nash · 1985
Earlier work this paper cites.
A limited memory algorithm for bound constrained optimization
R H Byrd, P Lu, and J. Nocedal · 1995
Earlier work this paper cites.
Implicit bias with ritz-galerkin method in understanding deep learning for solving pdes
Jihong Wang, Zhi-Qin John Xu, Jiwei Zhang, and Yaoyu Zhang · 2002
Earlier work this paper cites.
Numerical optimization
Jorge Nocedal and Stephen Wright · 2006
Earlier work this paper cites.
On the exact computation of linear frequency principle dynamics and its generalization
Tao Luo, Zheng Ma, Zhi-Qin John Xu, and Yaoyu Zhang · 2010
Earlier work this paper cites.
Fourier-domain variational formulation and its well-posedness for supervised learning
Tao Luo, Zheng Ma, Zhiwei Wang, Zhi-Qin John Xu, and Yaoyu Zhang · 2012
Earlier work this paper cites.
Neural tangent kernel: Convergence and generalization in neural networks
Arthur Jacot, Franck Gabriel, and Clément Hongler · 2018
Earlier work this paper cites.
Frequency-aware reconstruction of fluid simulations with generative networks
Simon Biland, Vinicius C Azevedo, Byungsoo Kim, and Barbara Solenthaler · 2019
Cited alongside, same era.
A phase shift deep neural network for high frequency wave equations in inhomogeneous media
Wei Cai, Xiaoguang Li, and Lizuo Liu · 2019
Cited alongside, same era.
Towards understanding the spectral bias of deep learning
Yuan Cao, Zhiying Fang, Yue Wu, Ding-Xuan Zhou, and Quanquan Gu · 2019
Cited alongside, same era.
Machine learning from a continuous viewpoint
Weinan E, Chao Ma, and Lei Wu · 2019
Cited alongside, same era.
Theory of the frequency principle for general deep neural networks
Suggested notation for machine learning
BAAI · 2020
Later among the works it cites.
Spectrum dependent learning curves in kernel regression and wide neural networks
Blake Bordelon, Abdulkadir Canatar, and Cengiz Pehlevan · 2020
Later among the works it cites.
Adaptive activation functions accelerate convergence in deep and physics-informed neural networks
Ameya D Jagtap, Kenji Kawaguchi, and George Em Karniadakis · 2020
Later among the works it cites.
A multi-scale dnn algorithm for nonlinear elliptic equations with multiple scales
Xi-An Li, Zhi-Qin John Xu, and Lei Zhang · 2020
Later among the works it cites.
Multi-scale deep neural network (mscalednn) for solving poisson-boltzmann equation in complex domains
Ziqi Liu, Wei Cai, and Zhi-Qin John Xu · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Tao Luo, Zheng Ma, Zhi-Qin John Xu, and Yaoyu Zhang · 2019
Cited alongside, same era.
On the spectral bias of deep neural networks
Nasim Rahaman, Devansh Arpit, Aristide Baratin, Felix Draxler, Min Lin, Fred A Hamprecht, Yoshua Bengio, and Aaron Courville · 2019
Cited alongside, same era.
The convergence rate of neural networks for learned functions of different frequencies
Basri Ronen, David Jacobs, Yoni Kasten, and Shira Kritchman · 2019
Cited alongside, same era.
A fine-grained spectral perspective on neural networks
Greg Yang and Hadi Salman · 2019
Cited alongside, same era.
Explicitizing an implicit bias of the frequency principle in two-layer neural networks
Yaoyu Zhang, Zhi-Qin John Xu, Tao Luo, and Zheng Ma · 2019
Cited alongside, same era.
Multi-resolution convolutional neural networks for inverse problems
Feng Wang, Alberto Eljarrat, Johannes Müller, Trond R Henninen, Rolf Erni, and Christoph T Koch
Cited in the paper.
Training behavior of deep neural network in frequency domain
Zhi-Qin J Xu, Yaoyu Zhang, and Yanyang Xiao
Cited in the paper.
The slow deterioration of the generalization error of the random feature model
Chao Ma, Lei Wu, and E Weinan · 2020
Later among the works it cites.
Deep frequency principle towards understanding why deeper learning is faster
Zhi-Qin John Xu and Hanxu Zhou · 2020
Later among the works it cites.
Drawing early-bird tickets: Towards more efficient training of deep networks
Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Yingyan Lin, Zhangyang Wang, and Richard G Baraniuk · 2020
Later among the works it cites.