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Variational methods are widely applied to ill-posed inverse problems for they have the ability to embed prior knowledge about the solution.
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Understanding and evaluating blind deconvolution algorithms
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Deep residual learning for image recognition
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Deep convolutional neural network for inverse problems in imaging
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Convolutional neural networks for inverse problems in imaging: A review
M. T. McCann, K. H. Jin, and M. Unser · 2017
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OptNet: Differentiable optimization as a layer in neural networks
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Convex analysis and monotone operator theory in Hilbert spaces
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Learning fully convolutional networks for iterative non-blind deconvolution
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