An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks

The MNIST database of handwritten digits

Y. LeCun · 1998

Earlier work this paper cites.

Linear inverse problems in imaging

A. Ribes and F. Schmitt · 2008

Earlier work this paper cites.

Optimality and stability of the k-hyperline clustering algorithm

J. J. Thiagarajan, K. N. Ramamurthy, and A. Spanias · 2011

Earlier work this paper cites.

Image denoising and inpainting with deep neural networks

J. Xie, L. Xu, and E. Chen · 2012

Earlier work this paper cites.

Auto-encoding variational bayes

Original

D. P. Kingma and M. Welling · 2013

Earlier work this paper cites.

Mixing matrix estimation using discriminative clustering for blind source separation

J. J. Thiagarajan, K. N. Ramamurthy, and A. Spanias · 2013

Earlier work this paper cites.

Generative adversarial nets

I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014

Earlier work this paper cites.

Adam: A method for stochastic optimization

D. Kingma and J. Ba · 2014

Earlier work this paper cites.

Image understanding using sparse representations

J. J. Thiagarajan, K. N. Ramamurthy, P. Turaga, and A. Spanias · 2014

Cited alongside, same era.

Deep learning face attributes in the wild

Z. Liu, P. Luo, X. Wang, and X. Tang · 2015

Cited alongside, same era.

Reconnet: Non-iterative reconstruction of images from compressively sensed measurements

K. Kulkarni, S. Lohit, P. Turaga, R. Kerviche, and A. Ashok · 2016

Cited alongside, same era.

Photo-realistic single image super-resolution using a generative adversarial network

C. Ledig, L. Theis, F. Huszár, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, et al · 2016

Cited alongside, same era.

Context encoders: Feature learning by inpainting

D. Pathak, P. Krahenbuhl, J. Donahue, T. Darrell, and A. A. Efros · 2016

Cited alongside, same era.

Unsupervised representation learning with deep convolutional generative adversarial networks

Compressed sensing using generative models

Original

A. Bora, A. Jalal, E. Price, and A. G. Dimakis · 2017

Later among the works it cites.

One network to solve them all—solving linear inverse problems using deep projection models

Original

J. Chang, C.-L. Li, B. Póczos, B. Kumar, and A. C. Sankaranarayanan · 2017

Later among the works it cites.

Deep image prior

Original

D. Ulyanov, A. Vedaldi, and V. Lempitsky · 2017

Later among the works it cites.

Semantic image inpainting with deep generative models

R. A. Yeh, C. Chen, T. Y. Lim, A. G. Schwing, M. Hasegawa-Johnson, and M. N. Do · 2017

Later among the works it cites.

Solving bilinear inverse problems using deep generative priors

Original

M. Asim, F. Shamshad, and A. Ahmed · 2018