
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization
Batch Normalization (BN) is a commonly used technique to accelerate and ...
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Convex Regularization Behind Neural Reconstruction
Neural networks have shown tremendous potential for reconstructing high...
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Spectral Decomposition in Deep Networks for Segmentation of Dynamic Medical Images
Dynamic contrastenhanced magnetic resonance imaging (DCE MRI) is a wid...
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Wasserstein GANs for MR Imaging: from Paired to Unpaired Training
Lack of groundtruth MR images (labels) impedes the common supervised tr...
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Degrees of Freedom Analysis of Unrolled Neural Networks
Unrolled neural networks emerged recently as an effective model for lear...
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Compressed Sensing: From Research to Clinical Practice with DataDriven Learning
Compressed sensing in MRI enables high subsampling factors while maintai...
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VAEGANs for Probabilistic Compressive Image Recovery: Uncertainty Analysis
Recovering highquality images from limited sensory data is a challengin...
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Neural Proximal Gradient Descent for Compressive Imaging
Recovering highresolution images from limited sensory data typically le...
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Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery
Recovering images from undersampled linear measurements typically leads ...
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Deep Generative Adversarial Networks for Compressed Sensing Automates MRI
Magnetic resonance image (MRI) reconstruction is a severely illposed li...
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Online Categorical Subspace Learning for Sketching Big Data with Misses
With the scale of data growing every day, reducing the dimensionality (a...
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Tracking Tensor Subspaces with Informative Random Sampling for RealTime MR Imaging
Magnetic resonance imaging (MRI) nowadays serves as an important modalit...
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Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors
Extracting latent lowdimensional structure from highdimensional data i...
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Recovery of LowRank Plus Compressed Sparse Matrices with Application to Unveiling Traffic Anomalies
Given the superposition of a lowrank matrix plus the product of a known...
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Innetwork Sparsityregularized Rank Minimization: Algorithms and Applications
Given a limited number of entries from the superposition of a lowrank m...
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Morteza Mardani
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