activity
20082022
most citedFourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

455 citations · 652 across the 10 of their papers we have counts for

collaborators

12 papers

cs.LG20223 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…

physics.ao-ph2022455 cited

FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Jaideep Pathak, Shashank Subramanian, Peter Harrington +10

FourCastNet, short for Fourier Forecasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at $0.2…

cs.LG20206 cited

Convex Regularization Behind Neural Reconstruction

Arda Sahiner, Morteza Mardani, Batu Ozturkler +2

Neural networks have shown tremendous potential for reconstructing high-resolution images in inverse problems. The non-convex and opaque nature of neural networks, however, hinders…

physics.med-ph2020

Spectral Decomposition in Deep Networks for Segmentation of Dynamic Medical Images

Edgar A. Rios Piedra, Morteza Mardani, Frank Ong +3

Dynamic contrast-enhanced magnetic resonance imaging (DCE- MRI) is a widely used multi-phase technique routinely used in clinical practice. DCE and similar datasets of dynamic medi…

cs.LG20195 cited

Degrees of Freedom Analysis of Unrolled Neural Networks

Morteza Mardani, Qingyun Sun, Vardan Papyan +3

Unrolled neural networks emerged recently as an effective model for learning inverse maps appearing in image restoration tasks. However, their generalization risk (i.e., test mean-…

eess.IV20198 cited

Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning

Joseph Y. Cheng, Feiyu Chen, Christopher Sandino +3

Compressed sensing in MRI enables high subsampling factors while maintaining diagnostic image quality. This technique enables shortened scan durations and/or improved image resolut…