
Materialseparating regularizer for multienergy Xray tomography
Dualenergy Xray tomography is considered in a context where the target...
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Learning the optimal regularizer for inverse problems
In this work, we consider the linear inverse problem y=Ax+ϵ, where A X→ ...
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Random tree Besov priors – Towards fractal imaging
We propose alternatives to Bayesian a priori distributions that are freq...
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Globally Injective ReLU Networks
We study injective ReLU neural networks. Injectivity plays an important ...
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Deep neural networks for inverse problems with pseudodifferential operators: an application to limitedangle tomography
We propose a novel convolutional neural network (CNN), called ΨDONet, de...
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Deep learning architectures for nonlinear operator functions and nonlinear inverse problems
We develop a theoretical analysis for special neural network architectur...
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Fitting a manifold of large reach to noisy data
Let M⊂R^n be a C^2smooth compact submanifold of dimension d. Assume tha...
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Matti Lassas
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