activity
20202023
most citedDemystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization

9 citations · 36 across the 11 of their papers we have counts for

collaborators

11 papers

eess.IV2023

SMRD: SURE-based Robust MRI Reconstruction with Diffusion Models

Batu Ozturkler, Chao Liu, Benjamin Eckart +3

Diffusion models have recently gained popularity for accelerated MRI reconstruction due to their high sample quality. They can effectively serve as rich data priors while incorpora…

eess.IV2023

Coil Sketching for computationally-efficient MR iterative reconstruction

Julio A. Oscanoa, Frank Ong, Siddharth S. Iyer +6

Purpose: Parallel imaging and compressed sensing reconstructions of large MRI datasets often have a prohibitive computational cost that bottlenecks clinical deployment, especially…

cs.CV2022★ 6 cited

Scale-Agnostic Super-Resolution in MRI using Feature-Based Coordinate Networks

Dave Van Veen, Rogier van der Sluijs, Batu Ozturkler +9

We propose using a coordinate network decoder for the task of super-resolution in MRI. The continuous signal representation of coordinate networks enables this approach to be scale…

cs.CL2022★ 2 cited

ThinkSum: Probabilistic reasoning over sets using large language models

Batu Ozturkler, Nikolay Malkin, Zhen Wang +1

Large language models (LLMs) have a substantial capacity for high-level analogical reasoning: reproducing patterns in linear text that occur in their training data (zero-shot evalu…

eess.IV2022

GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction

Batu Ozturkler, Arda Sahiner, Tolga Ergen +6

Unrolled neural networks have recently achieved state-of-the-art accelerated MRI reconstruction. These networks unroll iterative optimization algorithms by alternating between phys…

cs.LG2022★ 3 cited

Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers

Arda Sahiner, Tolga Ergen, Batu Ozturkler +3

Vision transformers using self-attention or its proposed alternatives have demonstrated promising results in many image related tasks. However, the underpinning inductive bias of a…