research
∙
05/25/2023
Demystifying Oversmoothing in Attention-Based Graph Neural Networks
Oversmoothing in Graph Neural Networks (GNNs) refers to the phenomenon w...
share
research
∙
04/25/2023
Learning Task-Specific Strategies for Accelerated MRI
Compressed sensing magnetic resonance imaging (CS-MRI) seeks to recover ...
research
∙
08/26/2022
Lower Difficulty and Better Robustness: A Bregman Divergence Perspective for Adversarial Training
In this paper, we investigate on improving the adversarial robustness ob...
research
∙
05/24/2022
Alleviating Robust Overfitting of Adversarial Training With Consistency Regularization
Adversarial training (AT) has proven to be one of the most effective way...
research
∙
05/13/2021
End-to-End Sequential Sampling and Reconstruction for MR Imaging
Accelerated MRI shortens acquisition time by subsampling in the measurem...
research
∙
06/05/2020
Scalable Plug-and-Play ADMM with Convergence Guarantees
Plug-and-play priors (PnP) is a broadly applicable methodology for solvi...
research
∙
09/04/2019