9 citations · 36 across the 11 of their papers we have counts for
4 papers · 1 filter
VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction
Arjun D Desai, Beliz Gunel, Batu M Ozturkler +6
Deep neural networks have enabled improved image quality and fast inference times for various inverse problems, including accelerated magnetic resonance imaging (MRI) reconstructio…
Noise2Recon: Enabling Joint MRI Reconstruction and Denoising with Semi-Supervised and Self-Supervised Learning
Arjun D Desai, Batu M Ozturkler, Christopher M Sandino +7
Deep learning (DL) has shown promise for faster, high quality accelerated MRI reconstruction. However, supervised DL methods depend on extensive amounts of fully-sampled (labeled)…
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
Arda Sahiner, Tolga Ergen, Batu Ozturkler +4
Generative Adversarial Networks (GANs) are commonly used for modeling complex distributions of data. Both the generators and discriminators of GANs are often modeled by neural netw…
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization
Tolga Ergen, Arda Sahiner, Batu Ozturkler +3
Batch Normalization (BN) is a commonly used technique to accelerate and stabilize training of deep neural networks. Despite its empirical success, a full theoretical understanding…