Recovery of Noisy Pooled Tests via Learned Factor Graphs with Application to COVID-19 Testing-Reference-Cited by-同舟云学术

Recovery of Noisy Pooled Tests via Learned Factor Graphs with Application to COVID-19 Testing

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Ben-Knaan Eyal Fishel¹,Eldar Yonina C.²,Shlezinger Nir¹

Affiliation:

1. School of ECE, Ben-Gurion University of the Negev,Be’er-Sheva,Israel

2. Faculty of Math and CS, Weizmann Institute of Science,Rehovot,Israel

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747150.pdf?arnumber=9747150

Reference28 articles.

1. Compressed Sensing

2. Efficient high-throughput SARS-CoV-2 testing to detect asymptomatic carriers

3. A Compressed Sensing Approach to Pooled RT-PCR Testing for COVID-19 Detection

4. Low-cost and high-throughput testing of COVID-19 viruses and antibodies via compressed sensing: System concepts and computational experiments;yi;arXiv preprint arXiv 2004 06774,2020

5. Practical high-throughput, non-adaptive and noise-robust SARS-CoV-2 testing;petersen;arXiv preprint arXiv 2007 09948,2020

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