
SUREMap: Predicting Uncertainty in CNNbased Image Reconstruction Using Stein's Unbiased Risk Estimate
Convolutional neural networks (CNN) have emerged as a powerful tool for ...
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Deep Learning Techniques for Inverse Problems in Imaging
Recent work in machine learning shows that deep neural networks can be u...
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Deep S^3PR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models
This paper introduces and solves the simultaneous source separation and ...
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Keyhole Imaging: NonLineofSight Imaging and Tracking of Moving Objects Along a Single Optical Path at Long Standoff Distances
Nonlineofsight (NLOS) imaging and tracking is an emerging paradigm th...
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Deep Optics for Singleshot Highdynamicrange Imaging
Highdynamicrange (HDR) imaging is crucial for many computer graphics a...
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An ExpectationMaximization Approach to Tuning Generalized Vector Approximate Message Passing
Generalized Vector Approximate Message Passing (GVAMP) is an efficient i...
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Unsupervised Learning with Stein's Unbiased Risk Estimator
Learning from unlabeled and noisy data is one of the grand challenges of...
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prDeep: Robust Phase Retrieval with Flexible Deep Neural Networks
Phase retrieval (PR) algorithms have become an important component in ma...
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Learned DAMP: Principled Neural Network based Compressive Image Recovery
Compressive image recovery is a challenging problem that requires fast a...
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Christopher A. Metzler
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