The Spectral Bias of the Deep Image Prior

On random weights and unsupervised feature learning

A. M. Saxe, P. W. Koh, Z. Chen, M. Bhand, B. Suresh, and A. Y. Ng · 2011

Earlier work this paper cites.

In search of the real inductive bias: On the role of implicit regularization in deep learning

Original

B. Neyshabur, R. Tomioka, and N. Srebro · 2014

Earlier work this paper cites.

Understanding deep learning requires rethinking generalization

Original

C. Zhang, S. Bengio, M. Hardt, B. Recht, and O. Vinyals · 2016

Earlier work this paper cites.

A closer look at memorization in deep networks

D. Arpit, S. Jastrzebski, N. Ballas, D. Krueger, E. Bengio, M. S. Kanwal, T. Maharaj, A. Fischer, A. Courville, Y. Bengio, et al · 2017

Earlier work this paper cites.

Exploring generalization in deep learning

B. Neyshabur, S. Bhojanapalli, D. McAllester, and N. Srebro · 2017

Cited alongside, same era.

Implicit bias of gradient descent on linear convolutional networks

S. Gunasekar, J. D. Lee, D. Soudry, and N. Srebro · 2018

Cited alongside, same era.

On the spectral bias of deep neural networks

Original

N. Rahaman, D. Arpit, A. Baratin, F. Draxler, M. Lin, F. A. Hamprecht, Y. Bengio, and A. Courville · 2018

Cited alongside, same era.

The implicit bias of gradient descent on separable data

D. Soudry, E. Hoffer, M. S. Nacson, S. Gunasekar, and N. Srebro · 2018

Cited alongside, same era.

Deep image prior

D. Ulyanov, A. Vedaldi, and V. Lempitsky · 2018

Later among the works it cites.

Training behavior of deep neural network in frequency domain

Original

Z.-Q. J. Xu, Y. Zhang, and Y. Xiao · 2018

Later among the works it cites.

A bayesian perspective on the deep image prior

Original

Z. Cheng, M. Gadelha, S. Maji, and D. Sheldon · 2019

Closest in time.

Frequency principle: Fourier analysis sheds light on deep neural networks

Original

Z.-Q. J. Xu, Y. Zhang, T. Luo, Y. Xiao, and Z. Ma · 2019

Closest in time.