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Understanding the Spectral Bias of Coordinate Based MLPs Via Training Dynamics

14 January 2023

Papers citing "Understanding the Spectral Bias of Coordinate Based MLPs Via Training Dynamics"

22 / 22 papers shown

Title
Adaptive Random Fourier Features Training Stabilized By Resampling With Applications in Image Regression Aku Kammonen Anamika Pandey E. von Schwerin Raúl Tempone 60 0 0 08 Oct 2024
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains Matthew Tancik Pratul P. Srinivasan B. Mildenhall Sara Fridovich-Keil N. Raghavan Utkarsh Singhal R. Ramamoorthi Jonathan T. Barron Ren Ng 126 2,440 0 18 Jun 2020
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis B. Mildenhall Pratul P. Srinivasan Matthew Tancik Jonathan T. Barron R. Ramamoorthi Ren Ng 129 2,592 0 19 Mar 2020
Frequency Bias in Neural Networks for Input of Non-Uniform Density Ronen Basri Meirav Galun Amnon Geifman David Jacobs Yoni Kasten S. Kritchman 84 185 0 10 Mar 2020
Empirical Studies on the Properties of Linear Regions in Deep Neural Networks Xiao Zhang Dongrui Wu 50 38 0 04 Jan 2020
Towards Understanding the Spectral Bias of Deep Learning Yuan Cao Zhiying Fang Yue Wu Ding-Xuan Zhou Quanquan Gu 106 219 0 03 Dec 2019
Deep ReLU Networks Have Surprisingly Few Activation Patterns Boris Hanin David Rolnick 84 228 0 03 Jun 2019
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies Ronen Basri David Jacobs Yoni Kasten S. Kritchman 80 218 0 02 Jun 2019
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent Karthik A. Sankararaman Soham De Zheng Xu Wenjie Huang Tom Goldstein ODL 59 104 0 15 Apr 2019
Stiffness: A New Perspective on Generalization in Neural Networks Stanislav Fort Pawel Krzysztof Nowak Stanislaw Jastrzebski S. Narayanan 129 94 0 28 Jan 2019
Complexity of Linear Regions in Deep Networks Boris Hanin David Rolnick 49 234 0 25 Jan 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks Zhi-Qin John Xu Yaoyu Zhang Yaoyu Zhang Yan Xiao Zheng Ma 124 519 0 19 Jan 2019
Occupancy Networks: Learning 3D Reconstruction in Function Space L. Mescheder Michael Oechsle Michael Niemeyer Sebastian Nowozin Andreas Geiger 3DV 251 2,907 0 10 Dec 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 154 1,454 0 22 Jun 2018
Sensitivity and Generalization in Neural Networks: an Empirical Study Roman Novak Yasaman Bahri Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein AAML 95 441 0 23 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,920 0 25 Aug 2017
Exploring Generalization in Deep Learning Behnam Neyshabur Srinadh Bhojanapalli David A. McAllester Nathan Srebro FAtt 162 1,259 0 27 Jun 2017
The Shattered Gradients Problem: If resnets are the answer, then what is the question? David Balduzzi Marcus Frean Lennox Leary J. P. Lewis Kurt Wan-Duo Ma Brian McWilliams ODL 73 406 0 28 Feb 2017
On the Expressive Power of Deep Neural Networks M. Raghu Ben Poole Jon M. Kleinberg Surya Ganguli Jascha Narain Sohl-Dickstein 63 790 0 16 Jun 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014
On the Number of Linear Regions of Deep Neural Networks Guido Montúfar Razvan Pascanu Kyunghyun Cho Yoshua Bengio 96 1,256 0 08 Feb 2014
On the number of response regions of deep feed forward networks with piece-wise linear activations Razvan Pascanu Guido Montúfar Yoshua Bengio FAtt 121 257 0 20 Dec 2013