45 citations · 71 across the 13 of their papers we have counts for
15 papers
Robust multi-coil MRI reconstruction via self-supervised denoising
Asad Aali, Marius Arvinte, Sidharth Kumar +2
We study the effect of incorporating self-supervised denoising as a pre-processing step for training deep learning (DL) based reconstruction methods on data corrupted by Gaussian n…
Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Data
Asad Aali, Marius Arvinte, Sidharth Kumar +1
We present SURE-Score: an approach for learning score-based generative models using training samples corrupted by additive Gaussian noise. When a large training set of clean sample…
Automotive RADAR sub-sampling via object detection networks: Leveraging prior signal information
Madhumitha Sakthi, Ahmed Tewfik, Marius Arvinte +1
Automotive radar has increasingly attracted attention due to growing interest in autonomous driving technologies. Acquiring situational awareness using multimodal data collected at…
MIMO Channel Estimation using Score-Based Generative Models
Marius Arvinte, Jonathan I Tamir
Channel estimation is a critical task in multiple-input multiple-output (MIMO) digital communications that substantially effects end-to-end system performance. In this work, we int…
End-to-end system for object detection from sub-sampled radar data
Madhumitha Sakthi, Ahmed Tewfik, Marius Arvinte +1
Robust and accurate sensing is of critical importance for advancing autonomous automotive systems. The need to acquire situational awareness in complex urban conditions using senso…
Score-Based Generative Models for Robust Channel Estimation
Marius Arvinte, Jonathan I Tamir
Channel estimation is a critical task in digital communications that greatly impacts end-to-end system performance. In this work, we introduce a novel approach for multiple-input m…