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08/06/2020
Learned convex regularizers for inverse problems
We consider the variational reconstruction framework for inverse problem...
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05/14/2020
On Learned Operator Correction
We discuss the possibility to learn a data-driven explicit model correct...
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02/28/2020
Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data
Recent work has shown the ability to learn generative models for 3D shap...
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05/10/2019
On the Connection Between Adversarial Robustness and Saliency Map Interpretability
Recent studies on the adversarial vulnerability of neural networks have ...
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01/17/2019
The Oracle of DLphi
We present a novel technique based on deep learning and set theory which...
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08/27/2018
Task adapted reconstruction for inverse problems
The paper considers the problem of performing a task defined on a model ...
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06/18/2018
Banach Wasserstein GAN
Wasserstein Generative Adversarial Networks (WGANs) can be used to gener...
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05/29/2018
